Utopia is other people

What is the most important part of a Utopian institute?

The simple answer is people.

The complex answer is also people.

There is an extraordinary distance between these two answers.

In the simple answer above, although it says people actually means Principal Investigators (PIs), the big scientists – and their big egos. It finds beautiful, oak-lined common rooms for them to drink vintage port from antique glassware whilst sharing ideas, before returning to their perfectly stocked labs where their teams are grinding out data to answer their next big question. In the background faceless individuals settle accounts, assess risks and empty bins. In this model science does gets done. But the question is who benefits and would actually find it Utopian?

The complex answer is that a Utopian institute is for all the people who work there and delivering science for the benefit of everyone. Whilst the outputs are critical, I am going to focus on the people side – an institute where everyone who works there feels they are part of the Utopia. The first consideration is that there is no hierarchy; everyone is valued, everyone contributes, everyone wins. Easy to say, complex to deliver: it needs a rethink about how we do science work.

This flatter, more egalitarian structure doesn’t mean different people don’t have different roles. Lab heads will set direction, train and develop early career researchers. Whilst research staff will spend their time doing experiments (and thinking about them), they will be empowered to have ideas and contribute to the direction of the project. Professional, Technical and Operational staff (PTO) will enable the science as an integral part of the team. Each person working at this Utopian institute would spend their time constructively, supporting the mission to do excellent science for the benefit of all and in so doing grow as a person. Growth doesn’t have to be constrained to in work, external interests will be celebrated. Flexibility will be encouraged – both in terms of working hours and working location.

All of which is easy to write, and since this is a Utopian vision reaching for the sky is not unreasonable. And since institutes are currently made up of people, what is stopping us?

A major hurdle is the existing research science career structure. Having lab heads immediately speaks to there being a hierarchy. By the nature of things, there will be some people who are more established than others. And as people grow in their career, it is not uncommon to want to progress (in salary at least), but also develop a leadership role. And there is an additional driver – the desire to lead one’s own research program. This is important, for scientific progress there needs to be direction and a program of work. One approach is to consider the trade-off between responsibility, seniority and freedom; later stage career staff will have more responsibility and this will be reflected in a degree of seniority – earlier career staff will have more freedom. One of the benefits of a flatter structure is that it would take away the dilemma about long-term postdocs. If someone is happy in their role, they could stay in that role, because they are valued for the skills and knowledge they bring without the pressure for ‘independence’. Experience and knowledge can and should be celebrated, as long as it is passed on. In the end, clustering of programs of work under the leadership of a single person will deliver the best science, but the leaders should not be placed upon pedestals and should be seen as enablers. Going Diva free is a first significant step to a Utopian institute.

One way to achieve Utopia is to remove sources of friction. Not forgiving it, but some of the diva behaviour comes about due to frustration with systems and processes. In my Utopia, the IT and other underpinning systems will work seamlessly minimising friction, allowing everyone to do their main role: letting HR support and train staff, researchers research and everyone to process their expenses as easily as paying a credit card bill.

I strongly believe that if you get the people right, the science will follow, but there is some infrastructure that would definitely enhance the Utopian experience. In house expertise and capability to deliver specific techniques (in my case as a biomedical scientist that includes imaging, sequencing and flow cytometry). As with the open research, these teams will also be integrated into the greater whole – providing a service, but collaboratively. A common stock of shared reagents and consumables wouldn’t hurt. Funding is a tricky question, some form of competition is important in refining ideas, but acquisition of funding shouldn’t take up more time and resources than it delivers.

There are also physical design elements to the building itself to ensure integration. The best approach is a hub and spoke model, with individual functions requiring quiet reflection at the end of the spokes and getting more collaborative as you approach the centre. This means individual offices at the end of the spokes, with labs along the corridors and meeting/ communal spaces in the hub. The entrance is via the hub to ensure random interactions between staff occur. The communal spaces need to have spaces for big meetings, but also smaller pods for discussion. The aim is to enable free mixing, the kind that leads to collaboration and discussion. And of course any Utopia would have a subsidised creche, decent transport links, places to park bikes and showers. Last but not least, a true Utopia has a nap room.

The final part is cultural enabling and contains my only non-negotiable element. The provision of tea (and coffee if you insist) and set times to drink it. And not just tea, but good quality tea, milk (that you don’t have to spend 20 minutes hunting down) and mugs of the right size (and thickness). Given the complexities of the rest of what I have proposed, this at least seems achievable.

This a competition entry about Utopian science research institutes. It didn't win sadly, but I stand by what it says - people matter

It takes a Village

First published in Times Higher Education

The greater prominence enjoyed by scientists during the Covid-19 pandemic has led to some individuals gaining a high profile – with the attendant praise and demonisation that this can bring. But these public figures are just the visible tip of a huge iceberg of effort taking place to combat the pandemic.

To convert one bright idea into 7.5 billion doses of vaccine will take a huge team of people. This includes not just the lab team developing and test the vaccine, but also the animal care staff enabling the pre-clinical studies, the safety staff maintaining a safe environment to work with a potentially fatal pathogen, the lab managers ensuring that essential reagents are available, the administrators preparing the relevant grant applications, the ethics boards reviewing the trials and the trial managers, doctors, nurses, med-students and volunteers. Not to mention the contracts team negotiating with equipment manufacturers, the accountants moving the money around, the security officers keeping the doors open and the communications experts informing the public of progress.

That is just at one institution. And the work is not performed in isolation: there are external funders, suppliers, manufacturers, regulators, toxicologists, shippers, couriers and warehouse staff, all of whom are vital to the process.

Unlike the standard image of an old white academic, staff in professional roles tend to be more diverse with more women, more BAME and more LGBT. But, in the UK, they will be excluded by the government’s proposed post-EU new immigration rules. This would be deeply counter-productive: if the pool of skilled individuals is reduced, there will be a clear impact on the ability to deliver cutting edge research, particularly in a time of crisis.

Highlighting the role of these critical core staff is vital. They are often under-represented in the media. For example, coverage of the recent UK pension strikes focused on the academics taking part, rather than on all the other higher education staff who shared the picket lines with them.

As well as not accurately reflecting science as a collective endeavour, a focus on individuals can, in fact, be toxic. Much of what is wrong with academia is driven by the narrative that it is a zero-sum game, where only one person can come out on top. This leads to the back-stabbing, bullying and bitchiness that characterises the very worst of our sector.

Now as never before, kindness in the workplace is critical. Developing the vaccine that the world so desperately needs can serve as a demonstration that great things can be done collaboratively rather than competitively, belying the inaccurate depiction of it in some places as a race between different universities. In the UK’s case, the race is supposedly between the University of Oxford and Imperial College London – but the fact that some of the ChAdOx (Oxford vaccine) trials are being performed at Imperial tells a very different story.

Thinking ahead, maybe we can use this time as a trigger to rethink the whole of academia. The first step is acknowledging that it is about more than the academics. It’s been said before, but when you look at the numbers, academia is actually the alternative career for science trainees: most enter other sectors – including academic support roles. All these paths should be supported and celebrated equally.

If none of the above persuades you, then consider this. Representing the team nature of science de-risks the process for the individuals, the institutions and the ideas themselves. People sometimes make mistakes, often unrelated to the science itself, but this can tarnish the idea. In an increasingly combative media space, any perceived fault can be manipulated to damage a broader theme. Demonstrating that science is collective removes one tool from the arsenal of those that seek to discredit ideas that have universal benefit, such as vaccination or combatting climate change.

The Wellcome Trust’s Reimagine Research campaign is currently looking into ways to rebalance the research space. But you don’t need to be a funder to make a difference. We can all play our part to make higher education kinder and more inclusive. Take time to say thanks. Reach out to teams outside your immediate remit. Be public in your praise, raising awareness of the whole team, not just the star signing. Applaud the whole community of effort.

Let me start and make an Oscars style acknowledgement of some of the amazing team at Imperial (and sorry if I missed you) – thank you Kasia, Kat, Kai, K, Krunal, Kostas, Catherine, Tessa, Anna, Hannah, Hadi, Michelle, Glenda, Genevieve, Paul, Paul, Carolyn, Ruth, Jennifer, Tom, Lesley, Sharron, Jesses, Leon, Aaron and Jo –I know that most people reading this will not know who they are, but without them we might never get back to work.

The Coronavirus Diaries

Head on over to Nature to read my diaries under Coronavirus Lockdown:

Week 1: Who I am https://www.nature.com/articles/d41586-020-01076-3

Week 2: On being a scientist without a lab https://www.nature.com/articles/d41586-020-01138-6

Week 3: On home schooling https://www.nature.com/articles/d41586-020-01293-w

Week 4: On getting distracted https://www.nature.com/articles/d41586-020-01323-7

Week 5: Things I don't miss https://www.nature.com/articles/d41586-020-01395-5

Week 6: People I do miss https://www.nature.com/articles/d41586-020-01476-5

Week 7: Getting ideas https://www.nature.com/articles/d41586-020-01555-7

Week 8: Getting rejected https://www.nature.com/articles/d41586-020-01624-x

Week 9: Taking a break not a holiday: https://www.nature.com/articles/d41586-020-01696-9

Week 10: Back to the lab again: https://www.nature.com/articles/d41586-020-01782-y

Week 11: Learning from my son: https://www.nature.com/articles/d41586-020-01867-8

Week 12: Unsocial Media: https://www.nature.com/articles/d41586-020-01948-8

First cut is the deepest

Grant rejection didn’t improve my scientific output, but it did improve my scientific career.

I had a reasonably frictionless track from undergraduate to PI, which I attribute to personal brilliance and dashing good looks, but was more likely a combination of hard work, luck and privilege. I had had some rejections along the route but nothing that felt derailing. There were rejected papers, but by and large rejected papers always find a home, maybe not as prestigious as I’d hoped, but a home nonetheless. I had also put out a few speculative job applications for posts that I was dramatically underqualified for, and was rightly turned down. But essentially, I got to lecturer without any big career rejections.
But rather than being a #humblebrag, I am trying to set the scene for what came next. As a freshly minted PI, flush with my own self-confidence, I submitted a research grant to a popular medicine-based science council. It came back with what I thought were reasonable scores and so I answered the reviewers’ comments, resubmitted and went to a conference in Thailand (again an important detail not just showing off).
On day 2 of the conference, I made the terrible mistake of opening my inbox. ‘We regret to inform you…’. Cue full on meltdown. To quote Nick Hornby, ‘I lost the plot for a while, then the subplot, the script, the soundtrack, the intermission, my popcorn, the credits and the exit sign’. I attribute this to several factors. I was away from my support network, 8 hours out of sync and it was pre-Skype so I couldn’t talk to them anyway. Secondly, it was the first big thing I had applied for that I hadn’t got. And finally, being new, inexperienced and somewhat melodramatic, I completely over-estimated the importance of any single piece of research funding on my academic career. There were a number of sleepless nights contemplating my ruined career and how I would never get over it.
I did get over it.
And whilst I wouldn’t go as far as describing it as a blessing in disguise, grant rejections (and time) have changed how I do my job. Rejection has had a humanising effect, having been ‘there’, I know what it feels like to undergo grant rejection and can sympathise better with other people undergoing the same experience. Having had (many) grant rejections and still being employed makes each individual rejection feel less make or break. I now have a longer perspective to see that some of my ideas are just plain bad and don’t deserve to be funded (obviously none of the ones currently under consideration), some ideas went to the wrong place and have now found a home, and some ideas are worth fighting for so that they get done, one way or another.
My first failed grant laid the foundation for how I now cope with future rejections and I am now failing better. There is a mourning period, which may sound like a strong term, but I think appropriate – if you don’t care enough about a grant, you are never going to submit it in the first place. After the mourning period, which I have managed to contract to 24 hours, I try to step back and take on the reviewers’ feedback as constructive. This is a challenge, but I have made progress since writing profanities about each reviewer’s parentage on the grant and then accidentally leaving this tirade on my desk for my students to see.
However good I get at failing, getting my grants rejected is still tricky – but never as traumatic as that first time.

(This first appeared in Times Higher Education)

20 Years at Imperial: what have I learnt?

On 1 October 1999, I walked out of South Kensington tube station in London, fresh-faced and ready to start my PhD. 20 years later as I walk out of the same tube station to the same campus of the same university (still fresh-faced I like to think), the question is, have I learnt anything? 

Spoiler alert – the answer is yes, but a guarded yes, from a staggeringly low starting point, like Marianas Trench low. Some of what I have learned is fairly niche and only useful if you work in a biomedical lab – like how to open a tightly screwed plastic tube with one hand whilst avoiding infecting yourself with influenza, some are a bit more generally applicable to having a career in science, especially if you are or want to run your own research group, and some grandiosely I think might be applicable to everyone.  

1.       School’s out. Working in a university, this may be a bit unnecessary to point out, but education never ends: we are continually learning and evolving. Even if you were able to recall all the facts from school into adulthood it is likely that they are now either outdated or completely irrelevant to the work you do. We need to retrain: to become parents, to become managers, to change roles, to retire gracefully. And for these new roles, there is no pass/fail test to say how well you have done, it is all a bit woolly. So we need effective strategies to learn for life: both for ourselves and for the others – students, children, co-workers – that we might need to train.  

2.       The skills to pay the bills. The skills you need for your PhD are not enough for the rest of your career. Being good in the lab or field or computer terminal is important, but at some point, you need more. You need social intelligence too (sometimes called soft skills): being able to work with other people. A lot of the PhD might focus on generating scientific results but given that most PhD students leave academia (estimates are between 95 and 98%) it is important to develop your whole self. 

3.       The Future’s so Bright I gotta wear shades. As Professor Martyn Kingsbury (Head of Imperial Education Development Unit) puts it so eloquently: your PhD is when you move from being a consumer of knowledge, learning what other people have done, to a provider of knowledge, producing data that other people will have to learn. My first experience of this was during my BSc project: I was looking at my squashed flies and feeling a bit uncertain about what the point of it all was when my supervisor came into the microscope room and said: “you see that, the thing you have just done – you are right now the only person in the world who knows that”. And that is what science is about, that flash of discovery, that satisfaction when the pieces of the puzzle fit together, the glow that however briefly you are the only person in the world who knows something. Doing a PhD had some of these moments and now as a lab head, I try to guide others to have them too. 

4.       Race for the Prize. The standard metaphor is that a PhD is a marathon not a sprint. But this draws on the wrong sport. A PhD is much more like a football season. It’s about consistency over a longer period, not constantly winning – you can even lose occasionally and still do well. The football analogy can be stretched a bit further over the length of a career, with each year a chance to reset and start fresh. One of the advantages of being in science for a longer time is that you get to see projects through to fruition. The ideas that you have which were initially rejected can be polished up, resubmitted and eventually find a home. 

5.       We’re going to be friends. I consider myself incredibly fortunate to work at Imperial, this is fundamentally driven by the people. I have met and worked with brilliant, kind, funny, supportive scientists, without whom this job would not be half as good. This connection began during my PhD and my fellow students now form the nucleus of a collaborative and supportive network that spans from Brisbane to Cardiff. Nurture your friendships. 

6.       Don’t Leave. No one ever really leaves Imperial. I did briefly try. For three years between 2008 and 2011, I worked at St George’s in South London. Luckily, I ignored the churlish temptation to say something along the lines of “screw you guys, I’m leaving”, as three years later I was back again – albeit one floor up from where I had been before. The science community in London is quite small, everyone knows everyone. This can be great because the network you build can help you out in all sorts of unforeseen ways. But it does necessitate some care, the person who you complain about one day, may end up being your office buddy the next.  

7.       London calling. I spend a lot of time dashing between St Mary’s Campus in Paddington and the mothership at South Kensington for some or other meeting. But this isn’t as onerous as it sounds, as I get to walk through Hyde Park and see the changing of the seasons. Which is just a fragment of the amazing things just on our doorstep. A lot of which is very easy to miss in the daily grind. But make time, go for lunch in the remarkable Art Deco café at the V&A, and if that is too far – go to the physics building for a cup of tea for fantastic views across Hyde park and beyond. 

8.       9 to 5. One of the best things about doing science is also the worst. Science is open-ended, fascinating and mostly you get to set the direction of what you are exploring so build on your interests. But this can mean that you can end up thinking about work all of the time, with no defined beginning or end of the day. Which is fine when things are going well. But when the inevitable setbacks pile up, there can be little respite. It can often feel like the best approach is to just do more work. At times like these, stepping away from the bench, taking some time out, for example by going for a run in one of London’s parks can help. 

9.       Life happens. In the process of doing my PhD, I met my future wife. While doing my postdoc, we married. When I started my group, I also started my family. And just recently there has been my first lab marriage (not actually in the lab, though I did offer to give the bride away). If you are too busy focussing on the job, you will miss these moments. 

10.   When I grow up. It is very easy to look at other people further down the track than yourself and assume they had life mapped out from the outset. This isn’t helped by the endless social media bombardment of success, which luckily didn’t exist when I was starting. Looking back, my career looks fairly linear, but at no point during my PhD did I think I would want to run a research group at the same university. I wrote up and then applied for a whole range of different jobs. In the end I took a postdoc position, mostly on the rationale that I had trained in science for three years, so I ought to see what it was like as a job. Even then I didn’t look much further forwards. I certainly didn’t have a single topic of research I wanted to work on. There is no harm in having a vague plan but being open to opportunities is vital. 

So in summary, have fun. Take time out, make friends, work to live rather than live to work. This way you will get the most out of your PhD and beyond. 

Post Script 

I was asked whether anything at Imperial has changed. Beyond my being older, the biggest change has been the space. The buildings have had a massive overhaul in the last 20 years, going from quite tired to shiny and new. I miss the old Holland Club and Southside bars, but I think that is more nostalgia for a time when I could pop out for a drink (or two) after work without having to race home to collect the children.  

My ability to predict the future is extremely low, things never quite work out as I imagine them. I honestly do not know what the next 20 (or even 5) years hold. A blend of opportunities, successes, disappointments, tantrums, scientific breakthroughs and scientific dead-ends no doubt, backdropped by a cast of wonderful colleagues and students. 

PS - can you name the 10 artists that sang the 10 lessons?

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How to win a research grant: Hone your sales pitch

I tend to think of my lab as a small business, with me as the entrepreneur at the helm – although I am probably closer to Del Boy Trotter than to Mark Zuckerberg.

This is just one of the many tortuous analogies I use to make sense of an academic career (because, let’s face it, academia doesn’t make much sense). Grants are the sales pitch that shore up the lab’s cashflow, and while I am not advocating passing off Peckham’s tap water as spring water, even genuine spring water won’t sell unless you market it properly.

As such, your grant applications have to target the customer. What complicates matters is that there are at least two different customers, with different requirements. Your sales pitch needs to be detailed enough to convince peer reviewers that you know what you are doing, but it also needs to be exciting enough to convince the panel to select your application ahead of other, equally scientifically valid, proposals. Here the lay summary is key. Sure, it is mislabelled: no lay person is ever going to read it. But it is your chance to sell the project to the panel.

Within a small business model, you also need to consider the cost of application. Our most precious commodity is our time. The endless hours absorbed by grant writing could be spent teaching, researching, writing papers or even having a life outside work!

The decision regarding whether to bear that opportunity cost should be taken in light of consideration of the chance of success versus the return if funded. Small grants with long application forms and a low hit rate should be ignored, no matter how desperate you get. I keep a tally of grants I have applied for, recording the grant value and the time invested. This has helped me to concentrate my efforts.

The sales pitch mentality stretches to how I review grants. I want to know what I am buying. First and foremost, I want to see a hypothesis. Not buried on page seven after the justification of resources, but on page one, line one, in bold. I then want my pulse quickened with a unique selling point. Why does the work need to be done? If it is a fundamental question, why does it need answering? If it is translational, how will answering it make the world a better place?

If that isn’t clear, no amount of technical competence will save you. So get out there and get selling!

This was first published in the Times Higher Education

#FailTales: Beyond resilience

A career in research is riddled with failure. The fact that there is a blog series about academia entitled #failtales suggests that failure in research is common. If the idea of failure being part of academia comes as a surprise to you, you are either too early on in your career to have been beaten down by it – in which case my condolences - or you are so hyper-successful that it has never impinged upon your exponential upward trajectory – in which case we are now mortal enemies.

First things first; it is OK to fail. Science isn’t easy. Science careers are not easy. We therefore need ways of dealing with failure.

Black Swan

I’ve recently been reading Antifragile, a book by Nicholas Taleb who is a self-styled errant business philosopher. His other book, The Black Swan, is about the surprising frequency of rare, extreme events and the disproportionate impact they have: the book takes its title from the fact that black swans exist, even if you have never seen one, i.e. absence of evidence is not the same as evidence of absence.

Antifragile

Antifragile takes this idea further, exploring how to deal with these random events. The book is not an easy read, but the underpinning message is revolutionary. In between the weird analogies about Fat Tony, a prominent character of the book who embodies the anti-intellectual trader who understands risk without theories, and references to obscure Greek Philosophers, Taleb makes a case for changing our approach to extreme events.

The author splits the world into 3 categories: fragile, resilient and antifragile. Fragile systems respond very poorly to extreme events, and according to Taleb this includes high finance and research that is directed with a particular result in mind. Resilient (or robust) systems, including opportunistic research and privately owned businesses, can cope with such extreme events and recover after they have occurred. Antifragile systems actually benefit from these same extreme events. His examples of antifragile systems include the net economic value of Silicon Valley tech start-ups and the net democratic value of feudal city states, both of which are characterised by agility in the face of changing conditions because of their relatively small size. They also benefit from having a large number of starting options upon which selection can choose the fittest. Interestingly a recent study in Nature suggested that scientific disruption is driven by small rather than large teams (https://www.nature.com/articles/s41586-019-0941-9)

So how does antifragile link back to scientific careers?

Failure is the linchpin of success.

Without some ideas failing, no ideas are going to succeed. This is very much in line with what Jon Tennant says in his article about the scientific record. Without better knowledge of what went before, we as a community are doomed to repeat ourselves.

A nuance of this is that failure is required to optimise an experiment: nothing works first-time. One of my more useful contributions to science literature was a technical note about in vivo imaging; a technically challenging process that is published in static beautiful images in a way that says, “this is easy, everyone can do this.” In actual fact, it turns out that there are a number of ways to mess it up. We managed to do all of them; fluorescent mouse turds, reflective ink in the pens we used, mice that were scientifically speaking too hairy, not enough anaesthetic, and so on. It would have been really helpful if someone had made this clear earlier. Only through failing were we able to get the studies to work and publish our own beautiful images, though it seems a shame that we failed to mention the pain we had been through to get them.

There is of course a separate conversation about failing fast, when it is right to drop a project if it isn’t working, and how information about the failed project can then be shared. Alternative publishing models and partial paper repositories where things can be put together from a group of studies are appealing, but they aren’t fully viable yet.

Back to the failure.

The aim of antifragility is to go one step further and make setbacks beneficial. It is easier to see how this works at a systems level. My failure and its publication helps other people. Likewise, in the context of grants, there have to be winners and losers – competition is important. If the system is working properly, only the strongest ideas survive and thus the field moves on. While that is great for research as a whole, what about me and my career?

At an individual level, how do you become antifragile? The aim is to make every situation a win-win. Taleb describes a barbell – a bimodal distribution of risk, basically reducing the cost of failure. He says “If I have ‘nothing to lose’ then it is all gain and I am antifragile.” For example, if you are going to invest in a project, reduce the emotional cost and make sure the return is high. Likewise, for antifragility in terms of experimental design, plan your investigations so that the outcomes are always interesting, rather than tightly focused on a hoped-for outcome.

We all fail. Grants are rejected. Papers bounce. Experiments explode. It is clear that we want to avoid the extremely negative impacts of failure. Part of this is moving away from fragility: not having our happiness and mental well-being pinned to a single outcome outside of our control. This means we need to move up the spectrum towards resilience. To achieve this, we can do a number of things: have a growth mindset, don’t take things personally, and build a good network of support for a start. Moving beyond resilience, antifragility can be built into your career. Place yourself so that regardless of external events, you succeed (or at least fail less). This involves not tying yourself to one single idea, too narrow a research field, a single funder: instead, hedge your bets strategically so that if one area goes down, others may be coming up. This is not easy, but at least thinking about it may protect us the next time failure calls.

This first appeared on Digital Science

Enter the Lab

So, there I was, pipette in hand, doing actual labwork for the first time in a year. How had it come to this? When I started out, I was convinced I was not going to be one of those PIs who is never in the lab: a common sentiment if you speak to late stage postdocs/ early stage PIs. My initial determination to stay lab active was in part caused by the disconnect between the training you receive as a post-doc and the reality of being a PI. Labwork so dominates the life of the postdoc that it is hard to imagine a job without it, skewing your sense of what a PI does and should be doing.

It can be tricky to come to terms with but as you progress in academia your job is no longer at the bench. There is a blunt reinterpretation of Adam Smith’s division of labour: “why have a dog and bark yourself”, which means you can’t do everything. As the leader of the group, your main responsibility is to support your team through ideas, funding and papers. Whilst it may be possible to have ideas and troubleshoot from the lab bench, there are some things that cannot be done, particularly writing. I find it very hard to alternate between bench and desk – and when I do try, fail to do both.

As time progresses, I have gotten to the point where my presence in the lab raises eyebrows and prompts various sarcastic comments along the lines of “labwork eh, try not to break anything”. Which I have to answer with as good grace as possible. However, there was one great occasion, when I had been teased all day by a postdoc about PIs not knowing anything, after several hours of this “banter” the same postdoc made a truly basic mistake in their experiments whilst my experiment went as planned, much to my amusement.

The move out of the lab comes with downsides. The lab is the heart of the group: it’s where all the gossip happens. Long experiments are great opportunities to get to know the team. Ensuring you have shared time together through other activities e.g. tea breaks, lunches and socials can help. As you step away from the bench, there is an inevitable skill fade, both in the techniques you do know and newer techniques that you do not. Losing lab skills is problematic on a number of levels. Psychologically, our success as postdocs was so closely linked to our success in the lab, losing the lab skill set before mastering the PI skill set is tricky. It can also affect our ability to lead in terms of legitimacy as group leaders which is in part based on our technical expertise, when this fades it can increase the ever-present imposter syndrome, but also not knowing how a technique works limits the ability to give feedback when it doesn’t. The best solution to this is to hire brilliant people.

There are still times when you can justify your presence in the lab, particularly in training. When you are getting established and it is just you and one or two other members of staff, the majority of lab know-how resides in your head. At this early career stage, there is a tension between good training and good results. You need to build a solid platform, so that your staff can function independently in the future: but every second you are not generating your first paper feels like wasted time, especially with the probation/ fellowship/ tenure clock ticking down. If you survive this first stage, the training can be self-perpetuating with existing staff training the newbies. This is very satisfactory but comes with the caveat that you need to think about quality assurance. The techniques I taught to my first PhD students 10 years ago have morphed over time. Normally this is for the best – things change after all, but it is worth checking occasionally. The training role never entirely disappears, because people selfishly leave from time to time and unless you have a succession plan in place take all that knowledge with them.

It is really hard to strike the balance. There are times when you are best out of the lab and other times when your presence in the lab might be the key difference between success and failure, or at least helping limit the levels of stress that your team have during bigger experiments. Erring on the side of absence builds independence in your team much more quickly – though this can be tough on them. One approach is to treat yourself to some labwork every now and then. Especially if you pick something that you can still do, that generates quick, easy results for use as preliminary grant data. These short bursts in the lab are refreshing. Unlike a PI’s day which involves some meetings, thinking a bit and maybe some writing, labwork has a set timetable with a clear endpoint to the day. Labwork can be simple and clean and it is reassuring to still be good at something, since a lot of being a PI involves external forces telling you are rubbish. It can also remind you why you got into science in the first place, especially if you generate some novel data. But lab time is best treated as a luxury rather than a key part of the job.

There are also upsides to leaving the lab behind. We tend to paint our lab time in a rosy shade as the best time of our life. But if you go back for longer than a day or so, you remember that it can be frustrating, especially when things don’t work. But more importantly, being the head of a lab enables you to do more of the research you want to do. As an early career researcher, you are working on someone else’s project and there is just one of you. When you get your own lab, you can put as many people as you can get funded onto the tasks you want to do. You also spread your losses, if it is just you, when an experiment fails it is devastating, when there are 5 people working for you, any one failure is offset by other successes.

The fact is that your role changes. As your group grows there is less need for you to be in the lab (and this is ok). You have to come to terms with the fact that most of the time you are best serving yourself and your team outside the lab. So if you are not leading a group yet, enjoy the labwork while you can because, as odd as it may sound right now, one day you will miss it.

This article first appeared on Digital Science

How do you build resilience

This was a co-authored piece with Dr Cecilia Johansson (Imperial College London)

At the recent British Society for Immunology (BSI) Early Career Training session in London, we were tasked with talking about tools to help immunologists improve their resilience. This was identified  by the BSI’s ‘Careers in Immunology’ report as an area that early stage (and middle and late stage) immunologists struggle with throughout their careers. So you probably don’t need us to tell you that a career in science can be difficult. Whatever stage you are at, there are always new hurdles to surmount and rejections to overcome. Part of the phenotype of the successful scientist is resilience: resilience in the face of experiments failing, resilience in the face of papers being rejected, resilience in the face of short term contracts, minimal wages and a terrifying lack of job security. As resilience is "the capacity to recover quickly from difficulties" – how do we build/enhance our resilience?

We have identified three sources of resilience that you can draw upon: within yourself, outside yourself and outside your work.

The Struggle Within

The first source of resilience has to come from within yourself. There are a number of tricks that we think can help:

1. Mindset. Carol Dweck is a Professor of Psychology at Stanford University; in her book MindSet,1 she identifies the strength of a growth mindset, which means looking for the opportunities to improve yourself in any situation. So instead of saying ‘reviewer 2 is an idiot’, reframe the situation to say ‘how could I have made my writing more clear so that even reviewer 2 could understand it’.
2. Other people. Other people’s success can be a source of strength, or not: we have two different approaches to deal with it.
   1. Never compare up (John’s approach). With the internet to hand you don’t have to look very far to find a more successful immunologist than yourself. It is then very easy to slowly sink into despair as you read their endless CV of success. Don’t do this! Alice Prince at Columbia very clearly describes how people’s CVs are not an honest reflection of the route they took.2
   2. Inspiration (Cecilia’s approach). Use amazing people around you as role models. Have a lot of them and use their skills/behaviour/mindset as motivation.  
3. Behaviour. It is not what happened, it is how you react to the situation that decides the amount of resilience needed. Your values, mindset, beliefs, and current state of mind all influence how much resilience you have: when you are super stressed and over-worked it is much harder to cope. Reflect on how and why you react to a particular situation and think of how you can improve your coping strategies.
4. Celebrate. Make a point of celebrating successes big and small: papers, grants, experiments for both yourself and everyone around you. Apply the perspective of time to your progress: taking a longer view smooths out the lows and demonstrates an upward trajectory. Pause and take stock of the past three months, one year, five years and identify what went right.
5. Make plans. It is difficult to assess your progress without a plan. What do you want to achieve in the next three months, one year, five years. The granularity of the detail can fade as you look further into the future.
6. Pause and take care of yourself. In a stressful life/period, it is very easy to forget yourself. Find ways of manage your time (as time is precious and we never have enough) and your stress levels. Mindfulness (essentially meditation) can be a very helpful tool. It doesn’t need much more than closing your eyes and focusing on your breath or the background noises for a few minutes to re-wind and re-set.

All of these approaches link to good reflective practice – studying your own experiences to improve the way you work. There are times when everything can get on top of you and you have to take time to step back. However, occasionally, it is not possible to do this alone and this is where you need to the second source of resilience, other people.

Everybody needs somebody

We all need support from other people. The Ancient Greek language has multiple different words for love/ support, and while the type of support we need most will vary from person to person and with time of life, these different types provide a useful framework for thinking about our interactions with others. This support can come from both within science and from your broader circle of friends and family.

Agape refers to love from a parent to a child, but more broadly reflects support from a senior figure to someone more junior. Don’t restrict yourself to one role model or mentor, you don’t even need to have met them (e.g. CJ looks to Cheryl Sandberg, COO at Facebook3; JT has learnt a huge amount from Stephen King’s book On Writing4). Take every opportunity to meet new and inspiring people. But also look inwards, most organisations (including the BSI) run mentoring programs. And remember different people will be useful for different types of advice/perspectives.

Eros describes the love of a partner. Now this is far from being a lonely hearts column, but we both draw great strength from our partners. The family network (partner, children, parents, cousins etc) is also a huge source of support.

Finally, but not least, Phillia love of a friend. Assembling a group of like-minded individuals is really important. Start in your PhD. Long hours spent moving colourless liquid around in labs are the perfect time to bond. Immunology is not a big field: as you progress with your career, it is amazing the times your paths will cross and re-cross. If nothing else, your PhD cohort are good for free beds in foreign cities. But the hope is that you can rise together on a common mutually supportive wave.5

Hit the road Jack

The final source of support is the realisation that this is just a job. If can feel all consuming, but it is still just a job. It helps to take a broader perspective. Again this comes back to good reflective practice. In parallel it is vital to have a life outside work (more work to live than live to work). This is not always easy, especially if you are juggling work and family commitments. But find outlets that you enjoy, without feeling the pressure to excel at them: bake but don’t aim to win Bake Off, run but don’t aim to win marathons. These other activities serve the same purpose as mindfulness – they break the loop when work is getting on top of you. Try to remember why you are doing/chose to do this job and the many positive aspects it brings.

A career in immunology has peaks and troughs. It’s ok to find it tricky and to admit to other people that you find it tricky. Recognising and celebrating the highs and learning tools to negotiate the lows can really help.

John Tregoning, Senior Lecturer in Immunology, Imperial College London. Twitter: @DrTregoning

Cecilia Johansson, Senior Lecturer in Respiratory Infection, Imperial College London. Twitter: @cjohansson_lab 

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Further reading

You can read more articles from John on his blog: drtregoning.blogspot.co.uk. References for the article are below.

1. Dweck, C. S. Mindset  the new psychology of success. Updated edition. edn,  (Random House, 2016).
2. Prince, A. Omissions from a National Institute of Health (NIH) biosketch. PLoS Pathog 14, e1006896, doi:10.1371/journal.ppat.1006896 (2018).
3. Sandberg, S. Lean in: women, work, and the will to lead. First edition. edn,  (Alfred A. Knopf, 2013).
4. King, S. On writing: a memoir of the craft. Scribner trade paperback edition. edn,  (Scribner, 2010).
5. Tregoning, J. No researcher is too junior to fix science. Nature 545, 7, doi:10.1038/545007a (2017).

No Laughing Matter: Use of humour in lectures

We were asked to come up with the best and worst examples of lecturing, either our own or those we’ve attended. Clearly my lectures are textbook examples of tertiary content delivery and probably deserve prizes (worth a try). So I thought back to when I was the recipient of lectures (a long time ago). But since I went to a research focussed university in the mid 90’s where teaching was at best seen as a chore, the quality was fairly universally m’eh. There was, however, one standout lecturer who I still remember, and not because of the content, something to do with action potentials in nerve cells (holy moly I remembered something), but because of his delivery style. Each lecture had a carefully crafted hilarious diversion (normally about walking in the Alps). This in turn got me thinking about using humour in lectures, which I try, and sometimes succeed, to do. Here are some tips:

1.       Simple is best. You don’t need to be Jonathan Swift to get a laugh out of 200 bored undergrads. To be honest, most of the jokes I use work as well with primary school audiences as they do with postgraduates (particularly my carefully curated library of pictures of snot). My most successful joke uses the power of slide animation to transform “B for boring cells” into “B for brilliant cells”, this even gets applause! But beware, jokes, if they work, disrupt the flow and it can take a couple of minutes to settle the room afterwards.

2.       Context is important. Students are not necessarily expecting humour and so may not process it as such. When, in a fit of pique, I told one cohort that their dissertations needed to be handwritten and have the first letter illustrated by monks, the course organiser had a busy afternoon reassuring them that this wasn’t the case.

3.       Be culturally aware. Most jokes work because of some common ground, knowledge or experience; which the students may not have in common with you. Age in particular is a big barrier. I started working at Imperial before most of the current students were born, so my references to pop culture often draw blank looks. I once told a PhD student that “I love it when a plan comes together” and they looked confused, apparently unaware of the wisdom of Colonel John “Hannibal” Smith.

4.       Visual jokes work, but can take time. I love cartoons and have tried to use them from a range of sources (Piled higher and deeper, sketching science and @redpenblackpen all being favourites). But cartoons take time to read - don’t just flash them up and expect instant gratification. Memes work better: since they come with a preloaded meaning, they tick the shared common ground box. They can even be educational – if Boromir is saying it, it must be true.

5.       Align with teaching. One does not simply throw in a joke and expect it to work: you need to link the joke to the content. Humour can be memorable, but it can divert memory away from what you are trying to teach. This is why 20 years later I can remember my physiology lecturer but not my physiology lectures. I managed perfect joke-content alignment once, by tenuously linking UKIP, Brexit and the EU to T cell immunology. 3 years later, the students came up and said they remembered my lecture from the first year – both the joke and the concept.

On the whole, humour is a useful tool, but there needs to be a thread, however unlikely between the learning objectives and the laughter.

This article first appeared in Times Higher Education

Turn off your e-mail and social media to get more done

Distractions are a fundamental aspect of the modern world, but we don’t have to become hermits to avoid them.

We are all busy, seemingly all the time, with a never-ending stream of e-mails to answer and meetings to attend. But are there better ways to do busy? Cal Newport, in his book Deep Work (Piatkus, 2016), says “yes”. Here’s what I’ve learnt from him.

Newport argues that, in the new world of work, the only thing we have to sell is our capacity to think rather than our capacity to do. But this ability to think does not come naturally or easily, and, unfortunately, the interconnected world that we live in throws big barriers in the way of big thinking.

Newport spends a lot of time exploring this point in Deep Work. But I suspect you need look no further than your swollen e-mail inbox or your back-to-back schedule to see that your precious time is being frittered away. And that is not counting social media, which has many ways to make us dumber: how many times have you lost a great idea, distracted by that little red Facebook notification?

The solution

Fortunately, Newport has a number of evidence-based ‘life hacks’ to combat this. Fundamentally, they come down to one thing: remove all distractions. You might think you are already doing this by turning off your phone occasionally. But you need to go further: don’t just turn off your phone; put it in a lead-lined box and bury it at the bottom of the ocean. Quit all social media. Isolate yourself from all modern life. Smash the Wi-Fi router. Move to a small island. Then, and only then, through a state of pure asceticism, might you get some work done.

However, this perfect state of deep thought might not necessarily be achievable if you want to keep your job, in which case some of the following suggestions might enable you to get the most out of your brain.

E-mail better

Shake the habit. E-mail is the worst attention thief. It has myriad means of misdirection, from the on-screen pop-up, to the envelope icon, to the alluring bold font in the unread e-mail folder. There is some ‘brain reward centre’ stuff happening with e-mail — it tells you that you are important and wanted, even if it is only an invite to write for a “presgitious new jorunal” [sic]. The easiest way to limit e-mail’s impact is to turn it off completely.

Burst transmission. That said, you still need to be in touch with the outside world. I try to limit myself to bursts. I can sustain focus for about 50 minutes, after which I reward myself with 5 minutes of e-mail, which inevitably turns into 10. No, this is not perfect and yes, resetting after 10 minutes is tricky, but it is much more effective than having the e-mail monkey on your back for the whole day.

Short and sweet. E-mail overload is universal and often exponential. ‘CC alls’, imprecise e-mails leading to immediate clarification and e-mail ‘tennis’ while trying to settle on a date all add to this burden. Making your e-mails concise and final means everyone wins. For example, instead of suggesting a time to meet, send a calendar invite directly. One question I don’t have the answer to is when to say ‘thank you’, balancing the need not to upset someone with not getting stuck in a further round of acknowledgment and counter-acknowledgement. Send better e-mail and ye shall receive better e-mail.

Do it later. E-mail is an insatiable beast; it feels like it needs immediate action: it doesn’t. Scan read, flag things for later and do it in batches.

Not now

Batching non-essential tasks can be applied to more than e-mail. I’ve found there is no way to stop the random thoughts coming, but it is possible to reduce their derailing impact. If a thought crops up, I scribble it onto a Post-it note and then batch busy work into times of the day when I am normally less productive.

Find a space

Your shared office maintained at slightly the wrong temperature, next door to a chatty neighbour with a penchant for pickled fish, might not be the ideal place to achieve the Zen of deep work. Try working elsewhere: libraries, cafes, at home. I get a surprising amount of writing done on the train to work — an added benefit of London commuters not talking to each other.

But it is not just about work. Making your brain better is more than 9 to 5. The Internet has invaded our lives to the extent that we cannot switch off. And you might argue that it is just downtime, but the habit of endlessly checking devices leads to a loop of inattention and a dilution of focus during working hours.

A lot of a scientist’s job relies on creativity, which in turn relies upon your subconscious doing some of the work. But it can’t do this when overloaded with cat videos, envious thoughts about your friends’ self-reported quality of life and pictures of someone else’s lunch. Stepping back from social and work media after certain times of day both help.

More radically, aspire to be bored. Put your phone away and if you have five spare seconds, keep them spare. Being click-baited to generate advertising income for unscrupulous publishers doesn’t do any good to you or the world.

Health warning

At the beginning of the summer, I tried the full ‘academic monk’ thing and failed. There were some mitigating circumstances for my lack of focus, but then again I’m sure there will be next summer, and the summer after that.

Clearing your head has clear benefits: better productivity; being more present with friends and family; brilliant ideas. It is also slightly addictive in itself — achieving deep focus and really working through a problem is intensely satisfying. We’re all working hard enough. It’s time to work smarter.

This is an article from the Nature Careers Community.

What are science?

Apparently we all fucking love science, or at least we love pretty pictures, anecdotal facts, chemical explosions and slightly preachy environmentalism.

However, science is none of these things. Science is the generation and testing of ideas; normally disproving them, in the process generating more ideas that need more testing.

Science junkies

Sadly, the day job of a scientist is nothing like the programs ‘Bang goes the theory/Tomorrow’s World/Johnny Ball Reveals All’ (delete as appropriate depending on your generation): in my 20 years being a professional scientist, there has been no time at work when I have blown anything up, thrown heavy weights into bowls of custard or put Mentos into bottles of Diet Coke.
To be honest, blowing things up at work is frowned upon and the management go to some lengths to prevent us blowing up the building (just another example of health and safety gone mad).
Highly visual demonstrations of chemical reactions are educational if phrased properly – if I do this, what do you think will happen and why? And these demonstrations can be effective for attracting the impressionable to a life of science. In effect, flashy chemical reactions are the gateway drug to scientific addiction.
At school we had a teacher who once a term gave us unrestricted access to the chemical store and a Bunsen burner; I imagined this was what it would be to be a scientist. Nowadays I don’t even get to do experiments, and yet I identify more as a scientist now than when I was doing my PhD as a space-filler before getting a “real job”.

Indoor work, no heavy lifting

So if the day-to-day of science isn’t setting things on fire, what is it?
It is immensely varied, and depends upon both the stage of your scientific career and the field you work in. But the main work of science is testing ideas. Some of which involves being in a lab, but most of which involves sitting in an office analysing the results from your experiments or coming up with new ideas because your experiments haven’t turned out as expected.
Since 99% of these ideas come from other people, another major strand is evaluating other people’s ideas and building on the back of them. And since other people need to evaluate the ideas we have, we need to be able to effectively communicate them, as written articles (papers), as sales pitches (grants) or in person (conferences).
So disappointingly, the day to day work of science is not so far removed from other professions, though we do get to wear a white coat occasionally. You need to be able to read, to write and, terrifyingly, interact with other people – very much none of the things that got most of us into science in the first place.