The Art of Pivotingby@BorisAdryan
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The Art of Pivoting

by Boris AdryanMay 3rd, 2016
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Most of you know me as <a href="" target="_blank">@BorisAdryan</a> on <a href="" target="_blank">Twitter</a> or from my technical Internet-of-Things blog <a href="" target="_blank">Opinions &amp; Experiments</a>. I’ve had a Medium account for a while, and I keep it for more subjective content. This is my second post:

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Most of you know me as @BorisAdryan on Twitter or from my technical Internet-of-Things blog Opinions & Experiments. I’ve had a Medium account for a while, and I keep it for more subjective content. This is my second post:

The Art of Pivoting, or less pretentious, how I changed from being a frustrated life science academic to using my skills as well-paid consultant for industrial engineering problems.

Setting the scene

It’s June 2016 and I’m packing my bags to move back to Germany after 12 years of academic research at the University of Cambridge and surrounding institutes, like the famous MRC Laboratory of Molecular Biology, forge of Nobel Prizes and home to eminent scientists like Watson & Crick, Sanger, Perutz, the ones you know from Jeopardy or biochemistry textbooks. I had come from a Max-Planck-Institute in Germany, where I had previously completed a life science PhD in slightly under three years. When I started my degree there in 2001, I had been the fastest student to fulfil the requirements for the Diplom in biology at my home university — and already had two peer-reviewed publications in my pocket. You may see the trajectory: success, efficiency, coming from good places, going to good places; the basic ingredients for a successful academic career.

Me in the “Model Room” at the old MRC Laboratory of Molecular Biology, with one of the original myoglobin structures.

Up is the only way

My wife and I had moved to Cambridge in 2004 to both do a brief postdoc abroad. Spice up the CV a bit, meet interesting people before settling down with a normal job back in the home country, that sort of stuff. The work I did was advanced and using technology not available to many people in Europe outside Cambridge at the time, but not revolutionary. However, combining experimental molecular biology and computational analysis of large biological datasets had just seen its first great successes, and I was a man in demand with my coding skills. Publications are the number one currency to climb the academic ladder and, by 2007, I had accumulated enough credit both in terms of scientific output as well as reputation in the field that I seriously considered an academic career for life.

Here, it may need to be explained to everyone who hasn’t spent time in academia why seriously considered is the appropriate phrase. It was a conscious decision for the long game. It’s the Tour de France or Iron Man of a career. You have to believe that you can do it and secure a position against all odds and a fierce competition. You have to be in it to win it. Chances are that you’re not going to make it, a fear that’s constantly present but there’s normally no-one you know who you could ask what life on the other side looks like, because failed academics -an arrogant view I held myself for a long time about those not making it- tend to disappear, ashamed and silent. Or get normal, unglorious jobs. According to my wife, who left academia when our second child was on the way, you got to be “stupid enough to commit to that”, given that academic salaries are poor compared even to entry-level industry positions, the workload is bigger, quite similar to that of running a start-up, and the so-called academic freedom is these days reduced to framing your interests into what funding bodies consider worth supporting.

Speaking of start-ups. 90% of start-ups fail. That’s a slightly better success rate than getting into the game that allows you to fight for a permanent academic position in the first place. In my cohort of Royal Society University Research Fellows, the success rate of obtaining a salary whilst building up a team was about 3%. What happens to the others who want to do science in academia? I’m sure many would not mind to stay postdoctoral scientists forever and pursue research in support of some other principal investigator (PI, a research group leader), but the system doesn’t cater well for that career track. Up is the only way. If you can’t make it to the group leader level, chances are that sooner or later you’re running out of funding. That’s because on the postgraduate level, especially after the financial crisis, there is a rather limited amount of money in the system that allows employment which resembles a regular job. Ambition, ego or an almost unreasonable love for the subject is the key driver for everyone else. Money is dished out competitively, and of course it’s considered an honour to be bringing your own salary to work unsocial hours for a rising star or established hot-shot. This sees many PhD level researchers leave academia sooner or later.

The postdoctoral level is attractive to employers in industry, as applicants are fully qualified scientists with hands-on experience in their subject.

This isn’t necessarily a bad thing. It’s just not what many of them had envisaged when they started their journey in university because they were hoping to do independent research in an academic setting.

Good times

I was fortunate enough to secure a University Research Fellowship from the Royal Society in 2008. Their package is great. Initial funding for 5 years (a good salary plus a small budget for commodity items and travel) followed by review, and then another 3 years. That’s pretty amazing. Know that other UK research councils might also give a young group leader money for an additional post to hire an assistant straightaway, but the overall funding period is just five years without any extension, and there is an enormous pressure to deliver. The Royal Society know about The Long Game. Eight years are over sooner than one might imagine in a research project, but it’s enough time to fail once or twice with a research idea and recover while getting back on your feet. One wrong strategic decision with any other startup package, and you’re history. Eight years is also sufficient to write grant applications, a process that consists mostly of waiting for an often negative outcome; and thus several attempts increase the chances to obtain actual research funding for the implementation of one’s ideas. I was quite lucky in that respect, as I had secured my first proper 3-year grant that paid for an assistant early in 2009.

The joys of starting a new lab: “Join me, I need more hands!” from my hiring page back then.

It was a great experience and I absolutely don’t regret my attempt in academia. I worked with some of the smartest people I’ve ever met and the learning journey was quite mutual. Originally trained as biologist and being a self-taught programmer, I benefitted considerably from hosting and supervising a postdoc and several students from computer science, engineering and mathematics. It was actually my very first PhD student who taught me the basics of machine learning, and my postdoc who introduced me to the art of agent-based models and large-scale simulations, methods that have been crucial to my professional success ever since. While my job had already turned to that of a research administrator and mentor rather than a hands-on scientist, my crew made sure I knew about their stack, including version control and other tips and tricks.

I’m not sure of the breakdown over time, but by 2015 I’ve had hosted a total of more than 40 researchers. At the peak of our success we were a team of 15 international, interdisciplinary scientists: postdocs, PhD students, Master and project students, and a few academic visitors. Papers were and, in fact, are still coming.

A painful realisation

The first few years of my Fellowship were a blast. Funding, research prizes, a continuous stream of talented applicants, and regular publications solely from our lab but also international collaborations.

Good times in the lab: Group members discussing results with collaborators.

In the first four years just doing science, albeit often in the form of writing grant applications or papers, was my primary activity. That turned into spending time worrying. The Royal Society is pretty clear that with accepting one of their Research Fellows, the Department and University commit to further that person’s career, cumulating in a permanent appointment. That seems to work rather well around the UK, except for Oxford and Cambridge, where Research Fellows are seen as a renewable resource that is naturally going to replenish itself, attracting great candidates for the opportunities these world-class universities can offer. In other words, it’s silently agreed and commonly understood that Research Fellows need to find a home somewhere else after they’ve generated revenue and prestige for Oxbridge. In my case, add into that mix a Department whose purpose was quite openly debated at the University at the time (“why have a Genetics Department if everyone else is doing genetics as well?”), a Head of Department who was widely seen as placeholder until it was clear what was going to happen, and the inertia of academic decisions in general…

Towards the 5-year review with the Royal Society, we were asked to provide proof of our employability, the standing in the field, collaborations within and outside the University, publications, and, importantly, any job offers. I took the opportunity to test the waters. Two good Russell Group universities had offered to host me for the remaining three years of my Fellowship, one even with a proleptic appointment.

Unfortunately, with a wife in management-level full-time employment and three kids, I was unable to accept any of these offers outside Cambridge. It became suddenly very clear to me that if I wanted to stay and things turned against me, I would have to consider alternative career paths. At the same time, it was clear that I had to invest every possible resource into obtaining an academic post at the University of Cambridge if I wanted to do academic science for life. I was entering a world of pain.

All systems 110% — at all times

There isn’t a better motivator than fear.

It’s a common joke that academics have a problem with time management because of their inability to say no. Everyone higher up the food chain tells young investigators to say no. No to teaching. No to committees. No to administrative duties. “Concentrate on your science, because that’s what you’re going to be assessed on”. At the same time, it’s very clear that if the choice is between two candidates, the better departmental citizen is more likely to be successful. In fact, my good citizenship was explicitly spelled out in my Head of Department’s recommendation letter to the Royal Society, while at the same time pointing out to me that I might want to consider a few less activities.

The rules about departmental citizenship are nowhere written. It’s just what you hear between the lines in comments about the poor performer who failed to do submit his part for a communal bid or the raised eyebrow about some lazy bastard who refused to teach. Unless the system discourages anyone with the ambition to secure a permanent post actively from taking on additional responsibilities, unestablished PIs are going to pour themselves into research, teaching, administration, outreach, you name it — at 110% of what’s healthy.

Add three little kids into that mix, and it may become clear why over time I’ve acquired a collection of meds vast enough to run a burn-out clinic.

Removing perspectives

Five years into my Fellowship, I felt more and more like a chased rabbit. Work was not about science anymore, work had become that abstract thing you need to do in order to secure a post. Also, with all the activities I agreed to do and to participate in, the time I actually spent doing my own hands-on research had become marginal. While my research group was at its peak and, from the outside, I looked like a very successful scientist, my job and my attitude towards it had completely changed. I began to hate my job.

Running a prolific computational biology research team at the University of Cambridge, I imagined it would be easy to switch into a management role in pharmaceutical R&D. I sent a few applications and had a few telephone conversations, but very soon it emerged that I did not have the relevant qualifications -that is: no business experience- to successfully run a group in industry. My wife explained to me that I had long surpassed the point-of-no-return, because just as you have to earn your stripes in academia to be trusted with directing research, you do have to have industrial project experience and considerable domain knowledge about drug development to be trusted with a R&D team. My most realistic chance would be a more technical role, at least to start with.

Swallowing my pride, I applied for Senior Scientist positions, or, as I thought of it, I applied to become a compute monkey for someone with a lot less academic credibility. However, while next-generation sequencing, gene expression analysis, pathway reconstruction and pipeline development were all happening in my own research group, I was clearly not the one who knew the nitty-gritty of their implementation anymore. The interviews were humiliating. “What’s your favourite Bioconductor package for RNA-seq?” — “Uh, I’d have to ask my PhD student for that.” “How do you force the precise calculation of p-values in kruskal.test?” — “I’d google it!”. Needless to say, I didn’t get a single offer.

Truly fucked: I was stuck in academia!

The moral of the story seemed very clear to me: Postdocs are great and appreciated in industry because they still know how to do stuff. As an academic group leader, you are essentially useless to industry. You can handwave your way through and claim management skills and theoretical knowledge, but most of what you do on an everyday basis (writing papers! navigate funding body websites! library committee! teaching students!) is highly irrelevant for industry.

It can always get worse

We got a new Head of Department in 2013. I’m not going to judge her. Let’s just say that the road to hell is plastered with good intentions. And I was in for the next shock: For years mentors and colleagues treated me as if my appointment was just a question of time, but unfortunately my Department had never had the resources to make me a real offer. Retrospectively, I can’t remember a single time that my mentors had told me to seek employment elsewhere, change institutions or even warned me that things might not pan out okay. We knew that the new Head had negotiated at least two posts, but -I rephrase one of my senior colleagues politely- it wasn’t clear whether she didn’t know or had not decided or had not even thought about what to do with them. And me. And the handful other junior PIs in the Department.

To bring the situation to a conclusion, I mentioned that a neighbouring Department had shortlisted me for interview for a post with them. I had hoped for a quick decision and maybe -unrealistically- even an ad-hoc offer while telling her the news over tea. The response could not have been more devastating for me: “Boris, that’s great. You see, jobs aren’t easy to get these days, and it would be nice if you could stay around.” She meant that without any malice. She was truly empathetic and happy for me. Nevertheless, I spent the rest of the day on auto-pilot, unable to come up with any reasonable thought.

Trust your gut feeling

Around that time I had started to interact with the maker community, and tinkering had become a hobby to take my mind of the sodding job. I already had a few good contacts in the tech industry, and by a weird chance encounter, was offered an extremely well-paid job in academic outreach and pre-sales of a tech company. It wasn’t the most exciting of all jobs, but offered almost the three-fold of my academic salary and could have been a door opener for many other opportunities within a large, international company.

My interview with that other Department went well. It was alluded to me that they were still debating, but I was probably very close to being offered a permanent post. In the end, it didn’t happen. I was close to a nervous breakdown. Left with no other perspective to stay in academia for much longer than the remaining three years on the Fellowship and wanting to cease the opportunity, I decided to shut down operations and accept the industry offer.

I let my mentors talk me out of it. In turn, I signed up for two more nerve-wrecking years struggling for a job that would never materialise.

I’m sure they acted with the best intentions. I’m sure from their perspective, it was too early to give up, that there was still good time to change my fate. However, they were unaware how costly that was for me emotionally, how often I suffered debilitating anxiety attacks.

A friend with whom I shared an earlier draft of this post commented on the above paragraph:

I am wondering — how qualified are these people to mentor you/us? They only know one side of the fence. They have grown into their established positions in an environment that was very different than today’s. And, let’s face it, they are mostly part of the establishment they created and maintain, and are unlikely to be ready to change it.

That’s a hard judgment and I’m not entirely sure it’s true for my mentors, neverthless I can’t deny that the same thoughts had crossed my mind before. Also, having three kids puts an entirely different economic pressure on an earner, and I’m not sure the gentlemen did appreciate that.

Losing more incentives

More than 45% of businesses to not recover from major disaster. I’d say the same is true for research groups. In October 2014, my personal friend and lab manager suddenly and unexpectedly died. He had been with me from 2009 and was responsible for much of the day-to-day operations in my lab, particularly the molecular biology and fruit-fly research that was going on in my group. It was a major blow for me and the lab. Besides the technical and organisational roles he had in our research, he was the experienced keeper of unwritten wisdom; and as a friend and my longest employee, my primary port-of-call when I had professional issues and doubts. Losing a friend I truly enjoyed working with meant the loss of another incentive to work.

While my Department was quite supportive to my grieving group members and provided some unbureaucratic administrative help in the short term, independent of this sad event, they let me down when it came to the longer term perspective a month thereafter.

The writing on the wall

Most research grants are awarded for a 3-year period. It requires the project lead to have employment with the University for the entire duration of the grant. I knew that I was in a difficult position with just two more years to go on my Fellowship and discussed the case with my Head of Department. This is where things got complicated. She had been ill-advised by the funder and was under the impression that I could simply add my final year’s salary as cost to that application. Following her encouragement, I wrote a proposal. The mistake was soon discovered by the funder and we were asked to retract the application, unless the Department was willing to provide an underwrite for my salary for the final year of the grant, if awarded. Twelve months of a mid-career level academic salary, in return for significantly higher overheads that the University would have received, and fuel for further research.

She said no. No reasons given.

In effect, that left my group without the ability to secure any funding to do our research. We had pilot data, we had experience with a new method, we had a game plan, we had relevant previous publications. And a Head of Department who deemed the work not worth supporting.

Two months later I had a formal appraisal. The conversation with the Head went well, she confirmed that my scientific strategy was reasonable, that my merits were strong, that I had a good reputation. And then we talked about the next steps.

Similarly to our first encounter, she was encouraging about all the wrong things.

Statements along the lines of “Oh, you have a strong interest about things outside the life sciences? That’s good. In case the plans with academia don’t work out.” didn’t really signal I was in for a job any time soon. We even talked about the skills that I would need to improve my employability by industry, and I had to explain the difference between myself and a web stack software engineer to someone who didn’t know a single line of code. My last formal feedback and mid-term development plan therefore states: “Should learn more node.js”. Great advice. I framed it. It hangs in my toilet now.

The endgame

A brief memo in January 2015 informed our Department that the two posts where going to be advertised in a matter of days, and that the competition would be open to everyone. Despite feeling miserable, I still wanted to go for it and submitted an application. However, after the treatment of the two previous years, I myself wasn’t even convinced anymore if I really wanted to work like that. I’m tempted to say that I tried my best during the interview, but I’m well aware that my lack of enthusiasm probably showed. I had just no fight left in me to act all “oh, I’m really looking forward to this very exciting opportunity…” or pretend to be a visionary scientist. They asked about the big questions of my science, as if that had not been laid out in the grant proposal they’ve retracted. Big questions… …my arse, as the environment and tone of the previous two years had me focus more on being employable, anywhere really, than to think about actual research.

I was fed up. The final no from the Department still hurt, but felt like a relief; much like getting out of a toxic relationship.

I had briefed my group. On the day when I was told that my application was not successful, I announced the closure of my laboratory.

Preparing for queen-sided castling

Wait what? You might think now. Did I not just tell you that I was not employable outside academia? How could I be relieved? Read on!

Unintentionally skilling up

In the beginning of 2013 I didn’t have a plan how to get my neck out of the noose. I just had a few geeky interests outside academia, funnily enough inspired by an educational toy computer invented in Cambridge that came out a year earlier: The Raspberry Pi.

  • I had started playing with the Raspberry Pi and soon thereafter with Arduinos and more professional microcontrollers.
  • I rediscovered the joys (and pains!) of low-level C programming, something I had not done in nearly 15 years.
  • I developed an interest in home automation and the hardware interfaces and wireless technology around it.

(If it’s not clear how these bullet points are connected — don’t worry: the geeks know).

A Raspberry Pi toy Linux computer with a high-power radio transceiver.

While building up expertise in these areas by attending hobbyist meetings as well as industry workshops, I found that I really liked to talk to people about it. Geeking around became a real hobby, with a surprising social component. Take that, academic loner without a life outside the lab! So I started going to Meetup groups, but also got certified as STEM Ambassador and went into schools to teach kids about technology and programming in CodeClub. And I volunteered to give my first presentations, sharing my geek interests at Raspberry Pi enthusiast meetings, called Raspberry Jams. This was probably the first time that I learned that my new interests around hardware and software actually had a name: The Internet of Things.

The biggest influence in what follows were the Internet of Things Meetups in London.

In a nutshell, a Meetup is a typically free-of-charge gathering of like-minded individuals, and there are many different ones on all sort of topics. The monthly IoT London Meetup usually features three speakers from different backgrounds, back then often a hobbyist, an artist and a professional, who entertain the group with short talks for ten minutes each. A great format for learning!

During one of my first Meetups an entrepreneur with a reasonable idea and a hardware prototype pitched his product. A convincing case, except from a data analytical perspective, his strategy seemed flawed. At first I was shy, mind you a biologist in a meeting of technologists, but when I informally voiced my doubts, I suddenly found myself as center of a conversation. People were taking me seriously!

Testing the waters in business

I started going to other IoT events, partly out of interest in IoT and the businesses in the field, partly to see what particularly the analytics field looked like. Sometimes I even volunteered to help out with name badges and running errants, in exchange for access to conferences that otherwise are charged at a premium rate. What I had heard through the grapevine was confirmed: Most out-of-the-box offerings around IoT data analytics were neither understood by the sales people, nor by their prospective customers. There was a distinct need for someone who understood data science and could communicate its principles in a simple and business-oriented way. That was me! After initially providing consultancy informally and often unpaid -remember, I was just a biologist with a geek interest- I finally registered a business. If you are into IoT, you may have heard of it: thingslearn.

thingslearn Ltd.: Data analytics, machine learning and context integration for the Internet of Things.

At this stage, IoT was still just a hobby and despite occassional commercial activities, I was still a full-time academic. Nevertheless, people started to take notice. In 2013 an open-source project called Node-RED was released, a visual programming environment for the Internet of Things. I had come across it at one of the IoT London Meetups and, together with friends from the same group, we were amongst the first to drive it to its limits and pester its developers at IBM with feature requests and bug reports. The developers referred to it as plumbing tool for IoT data, but how the plumbing is done remains very much a problem to the user. In the spirit of an academic, I sought to systematically test different cloud platforms for their functionality and ease of interaction with Node-RED. Access numbers to that section of my blog -back then still that of my research group at the University- went through the roof. CEOs of two IoT platforms asked for my time, wanting to know exactly what I liked and what I didn’t like — because it mattered. I had started to make myself a name in IoT.

Conferences — that’s where professionals speak, no?

In August 2014 I stumbled over a tweet by one of the Node-RED developers that, unfortunately, he was unable to deliver his presentation at an IoT conference in Berlin. Half-jokingly I mentioned that I was going to be in Germany for holidays anyway and that I would happily take his speaker slot. Within 30 minutes, I had an email from the conference organisers. Within two hours, I was planning my first talk at a professional IoT conference. September 2014 saw me wearing business-casual, fully mic’ed up with a stick-to-your-face headset, and ready to rumble. I made a ton of very important contacts.

Me. The first time wearing a shirt in a professional context.

Inspired by my success, I submitted a talk proposal to one of the best IoT developer conferences in the world: thingmonk. I could impossibly talk about Node-RED again, especially since its very developers were coming to the event as well, but I offered my genuine perspective of a big data practitioner from the life-sciences, and what our work on databases, minimally required meta-data, data standards, repositories and ontologies could teach the IoT. The talk was accepted and very well perceived.

It slowly emerged that people accepted me as domain expert for context-integration in the IoT — because nobody else was speaking about it.

From there, things went very quickly. I got invitations to talk about that subject at quite a few data science and IoT conferences. And to give you an idea of time: I held my O’Reilly webcast on IoT ontologies in May 2015, a week before I announced the closure of my research group and end of my academic career.

Moving in for the kill

Let’s rewind for a moment. Five months earlier, at thingmonk, I had a very good chat with one of the other speakers, the CEO of a London-based startup. I explained to her my doubts about academia, but also the doubts about my own ability to be successful in industry. She invited me for an internship, or better, to stick around and see what people were doing and how they were doing it, and offered me some tech training in her obscure programming language so I could see how work in the real world looked like. A week after my academic appraisal, the one that recommended I should learn more node.js, the week before Christmas 2014, I set up my laptop in a London office.

The startup environment was entirely different than I had experienced my job interviews with pharmaceutical companies. Everyone was googling Stackoverflow. People learned on the go, and they learned fast and delivered impressive production-ready solutions. But everyone was different and had a different skill set, and that difference was appreciated. My doctorate even made everyone assume that I surely would be the smartest person in the room. :-)

We forged a strategic partnership — not as business partners, but as friends.

It became clear that, if the academic shit really hit the fan, I was always welcome to come back. I would bring data science knowledge, and in turn I’d learn devops.

Pivoting like a boss

The moment my academic career was over, I contacted my friend. We had previously discussed collaborations that her and my companies could and should do if only I had more time. I was ready!

Over the next months, I took on a big hardware project and, as new skills, learned how to design printed circuit boards and how to optimise an embedded system for power saving. I took on a data science project, which exposed me to geo information systems and the algorithms and methods employed in GIS. And I learned how to do a pre-sales conversation, when the customer still needs convincing that data and analytics is the answer.

I keep this section short as there were other, still ongoing projects. To keep a long story short: Nobody expected me to know everything right from the start. People in industry are a lot more lenient than academics. And a lot more appreciative.

In academia we are taught to question everything and criticise everyone, whereas people in industry are foremost interested in how you help them with what you’re doing.

By summer 2015 I had fully transitioned into my role as Founder, Director and primary Doer-of-Things at thinglearn. That was enabled by my Royal Society University Research Fellowship, who supported me throughout the entire period. While my Fellowship was orignally awarded to do genomic research, the Royal Society allow people to develop in different directions, especially when there are potential commercial applications of the research. In fact, the Royal Society’s Business and Innovation courses, which I took in 2014 and 2015, teach out-of-the-box thinking and prepare academics for a role as founders and entrepreneurs. I’m infinetely grateful for that.

The time I spent investigating how the data sharing principles of modern biology may be used in an IoT context was thus a logical extension of my prior research.

No other funder would have allowed this. I was even further encouraged when the Royal Society invited me as advisor of their policy group for machine learning in January 2016, or to speak at a Café Scientifique about the data problems of genome research and IoT in Manchester coming July.

In the meantime, I had become a regular speaker at IoT conferences near and far. With my academic training in machine learning and data analytics, my geeky interest in technology and my passion for good user experience, I filled the void between engineers and marketing.

Preparing to move

In early summer 2015 I had spotted an advertisement for a professorship at a German university, focus: The Internet of Things. With their obsession in paper qualifications, I didn’t believe that an electrical engineering department would seriously consider me as a candidate. However, they did. I went through a series of interviews over a few months, everytime with people higher in the academic hierarchy than before.

A picture I took at a gallery when visiting for job interviews. You probably have to know Germany culture quite well to understand how this picture is very true.

My wife and I started looking around for houses in the area. Good schools, cheap houses, great quality of life — but not because of chosing or being able to afford the right neighbourhood. No.

This was Germany, a country in which the provision of good education is expected from the government, where cellars and attics and double-glazing are a minimal housing standard, and where the cost of living is so much lower than in the UK.

All things considered, we decided that, even if my wife wouldn’t be able to work, we wanted to move here again.

The professorship didn’t materialise. Or, let me rephrase that, I’m still waiting for the final outcome — eight months after the last interview and being sent occasional brief reminders that I’m still under consideration, but that the formal appointment is now in the hands of the local government... However, we definitely wanted to move back home after 12 years in the UK, project name box-it-for-Brexit, without having to rely on the mercy of some lengthy administrative process, and so I started to go through my LinkedIn contact list (which I grew to >500 IoT contacts in two years).

Through my continous outreach activities on Twitter and my personal blog, along with conference visits, giving talks and just being present whenever it was important, I was well known in the field. I sent out four more or less informal application letters to people I trusted — all four yielded invitations for interview.

In the end I signed a contract with a large German engineering company, where I’m going to do what I’ve enjoyed doing for the past couple of months: read, write and talk about IoT, analyse data, write code — with sufficient freedom to look at the bigger picture, and for a salary that even the professorship could not compete with.

Conclusions and lessons learned

It’s hard to conclude general lessons from n=1, myself. Let me try to summarise my views and recommend strategies anyway:

  1. The funding crisis is making an academic career increasingly difficult. Bad management kills peoples’ incentives to stay. Poor advice stops people from leaving.
  2. If academia and science is the 100% only thing you want to do in your life: Don’t get married. Don’t have kids. Relationships and family make you less flexible in terms of mobility. — Sadly, I’m only half kidding.
  3. Beware of the group leader level. You’re much more likely to be hired in industry if you’re still a postdoc with relevant hands-on skills.
  4. If you can do data science, you’re pretty safe. However, you’re competing against people with industry skills. It’s not enough to know just R. There’s a huge data science stack not often used in academic research. Learn as much as you can. Hadoop. Spark. Flink. Tensor Flow. These frameworks come and go, and you should at least be able to place them in the stack.
  5. Build a brand around your yourself: In the beginning you may be perceived as just an academic. Show the relevance of your skills and abilities to industry — I found speaking at conferences helps a lot!
  6. Be visible. I tweeted and blogged extensively about my views and analyses around the Internet of Things.
  7. Don’t be shy. Don’t be too proud. Talk to people. Get into their address book. Find people in industry who you trust. Ask for help.
  8. Identify domains outside your academic field that interest you. Get domain knowledge. It doesn’t matter what you are formally trained in, what matters is what you know. And that you can demonstrate adaptability.

I’m really looking forward to what the future brings. See you soon!