What I learnt from meeting 1000+ researchers

Over the past few years I have traversed through academia in a few different guises, first as a PhD student for about 5 years, then onto the traditional route of a post-doc, followed by a sales representative for a life sciences company and finally as the co-founder of ELISA Genie. It’s been a great journey and I’m constantly learning as I move through different facets of working with academics.

Currently I’m in year 3 of running my own scientific start-up, it’s a blast, I travel the world, work on new projects every week, attend conferences, but the most interesting part is where we help people with their research.

To take a few steps back, I was extremely chatty during my PhD, having a semi-outgoing personality helps, but what I also discovered, was how chatting to other scientists improved my research. This is obvious of course, but I am surprised at how many scientists still do not make the most of other researchers around them.

A question I commonly ask researchers is how many papers they read a year, it’s a straight forward question and leaves most academics sitting there, quelling over how many they read a week, not least to say a year. One of the most common answers I get is “I’d be lucky if I read 100 papers a year!”, which always amazes me! For the most part, these researchers publish in mediocre journals with a handful of papers a year if not every two years.

However, when I get to meet researchers that are publishing in high impact journals and pose the same questions, I usually get a response of “I don't know, 500+ papers a year?”. These researchers know their fields and fields related to their fields incredibly well and this shows in the output of their work. Publishing more consistently in better journals and more often than not running bigger labs with more funding. One Professor in particular, blocked out two hours every morning on their calendar, dedicated to reading papers.

However, there is always the anomaly, one Harvard Medical School Professor I met openly stated on stage that he never reads papers, to which the audience gasped and sat upright in their seats. However, the caveat for this researcher is that he attends hundreds of talks a year by constantly attending conferences. Which also suggests, that attending as many talk, conferences and seminars can also have a big impact on your level of science.

As we all know, it’s not what you know, but who you know. And academia is not an exception to this rule. Take for instance any top conference in your field and sit right up the top of the audience. 99% it’s where key piers in the field sit alongside the researchers that are about to present. But what is also interesting about this, is that they all know each other. Each commenting on the presentation of the other like they’ve seen the data before (where in most cases they have at a previous conference) and post-talks, sticking around to chat socially or later in the bar that night.

Networking in science is an incredible tool that all the top scientists use to accelerate their research. And what’s incredible is that mid-level academics do not do this correctly or even at all. Either they are too shy to go over and talk to keynotes or email about some idea or observation that they have.

One academic I’v chatted to, says they openly share results they have with other leaders in the field to see if they can replicate the results. Thus, leading to some incredible collaborations and higher impact journals.

I talk about romanticism in research a little later on, but something that stands out a lot is how some of the best researchers are both innovators & early adopters of new technology and applications that allows their research to take a new path or generate more data than previously imaginable.

For a long time and I mention this in our Ebook, “How to complete a successful PhD”, most scientists work in a A-B-C fashion or a color by numbers manner if you will. Looking at current research areas or pathways, then finding one node in the pathway and trying to figure out a small aspect of the pathway, hoping to get that Nature, Cell or Science paper, when they are really just aren't at that level.

However, when I talk to labs looking to push the envelope of their research, new technology is where their focus lies. What is the newest, fastest, most sensitive tool they can use to unravel their problem. This also follows into how they build their networks. Who can they connect with a leverage this technology that is not within arm’s reach to get more data.

A huge part of being a sales representative was meeting researchers in the lab. As a sales rep, a lot of your time is spent dealing with Post-Docs, PhDs and technicians who run the lab on a day to day basis. This side of research gave me a real insight into the mechanics of how really well-oiled labs work.

What really stood out for me, was the level of organization in high performing labs. These labs run to military precision. Everything is rostered, benches were organized, kept neat and you could see inventory lists on the freezers, so science could flow consistently without interruption.

Digital systems where in place, like Quartzy to track inventory and all their data was placed in Evernote for a digital lab book, where the data was available to the lab and PI for quick reference and data logging.

Most academics spend a lifetime working on the same project, protein or pathway, with little variance. A factory line of PhD after PhD making micro-improvements on the work of a previous PhD. Although this can be great to build a body of knowledge around an area. The overall contribution to the scientific community level’s off after a few years of academics testing the waters around a specific area. The sigmoid curve comes into play as academics get bored of their research area or they run out of funding.

Interestingly, academics, that jump into areas around their research theme was where I saw the most success. This happened either through networks with other researchers in their department, University or an external collaborator. This approach led to the researcher “Stepping Away from the Sun!” and having an holistic view of their research landscape. This also brought new ideas, applications and other streams of potential funding to the lab in order to answer their question.

Overall, networking, reading and looking for better technology seems to be a common theme running through the best labs and a key driver for success in these groups. Although I don't have stats on any of the above, hopefully these observations help with your research success!