In my Careers Spotlight Series I speak to a diverse group of post-PhD scientists who have taken non-academic career routes after finishing up their PhD.
Taking other career paths can be daunting and mysterious. In this series I hope to alleviate some of these worries by speaking to professionals that have been through it all!
Today's guest on the academic to non-academic careers spotlight series, I speak to Dr Gregorio Alanis-Lobato, a principal computational biologist working for Boehringer Ingelheim in Germany. I first met Greg when he was working as a dry lab biologist in London, modelling human embryo development, and I’m curious to know how he made the transition into the pharmaceutical industry.
Greg spent the early years of his career as a scientist in Mexico. He describes himself as a “Mexican scientist, read-a-holic, [who] loves track and field and loves computers”. These things combined led him to the National Polytechnic Institute in Mexico, one of the only universities that could offer a computer systems engineering career.
Jumping forward a few years, at Boehringer Ingelheim, Greg still uses computer systems to support his team in data-driven drug target identification. He explains that “my team and I support two therapeutic areas in the company; one is central nervous disease research and the other area is research beyond borders.
Central nervous diseases is an area that is mostly focused on psychiatric disorders, like schizophrenia or major depressive disorder. Research beyond borders, although often called a therapeutic area, is focused on exploring emerging science and technologies in support of different therapeutic areas.
However Greg’s journey to Boehringer Ingelheim has been rich and varied. Following his degree in Mexico, he originally wanted to work in the IT environment, and did do that for a while. He stayed in Mexico as a software developer and then interned with IBM Mexico. It was after this role that Greg became really interested in complex and biological systems. He carried out a masters in computer science and a PhD in computational biology at a university in Saudi Arabia. He then did post-docs at Johannes Gutenberg University in Mainz and then the Francis Crick Institute.
“I was really really happy in academia”. Greg tells me happily.
I ask what inspired the change.
The main driver turns out to be stability. “We were really looking for stability, and for a place that we could call home” explains Greg, who’s wife is Colombian. “many academic contracts are short”. His current role was found as an advert on LinkedIn, and the profile appeared to fit perfectly. Not only this, but the role was more senior, and permanent.
The focus of Greg’s scientific career had been revolving around complex systems. He studied protein-protein interactions; modelling the outputs of wet-lab experiments as networks - where the nodes are proteins and the interactions between them are represented by edges. Unfortunately however, these networks are incomplete because probing for the interaction between every protein in a complex organism like humans is technically challenging and costly.
One aspect to consider when changing from an academic to industry based position is how the CV is targeted to the job. I asked Greg whether he considered his skills in this way.
Greg believes that the skills fall into two areas; technical skills and soft skills. He says “as an academic, it is difficult to highlight the soft skills, but you have them, it's just a matter of digging deep into your CV and actually highlighting them”.
Although it’s essential to consider the soft skills, the technical skills are essential too. For his role, he believes they were looking for someone with experience on data analysis, more specifically actually on network analysis. These areas fit with Greg’s career history perfectly.
I try to summarise ‘Greg’s top three soft PhD skills’:
Scientific method - “you’re observing stuff, coming up with a question, doing research around that question then formulating hypotheses, experimenting, analysing data.”
Project management - “you’re in charge of several projects, so being collaborative and having project management skills are key.”
Teamwork - “as an academic, you also work with teams and you have to manage your PhD or postdoc project.”
Having seen his job advertised on LinkedIn, I ask Greg to delve deeper into the resources he recommends. He reiterates the importance of online networks.
“My one piece of advice would be to open a LinkedIn account and spend weeks fine tuning your profile, and start to grow your network. I’ve realised that it is super important, at least in the pharma world, to have a LinkedIn account because that allows you to connect not only with your peers, but also with potential business partners.”
These networks carry other strengths. Having a strong network can help with navigating the often-opaque world of salaries. Greg advises reaching out to contacts in similar industries to get a feel for what the salary range should be for a role. This can be vital when coming from academia where salaries can vary.
Greg tells me that networks are also incredibly useful for interview preparation. He suggests that contacts in relevant industries can give you tips for preparing for interview questions, especially for the odder questions that you don’t normally get when you apply for academic positions.
LinkedIn isn’t the only place for useful advice though. Greg tells me about a few more.
One is a series published by PLOS Computational Biology called “10 simple rules for” and they have 10 simple rules for a lot of things, like 10 simple rules to do a certain type of analysis, or 10 simple rules to choose between industry and academia. This can be very useful for people considering the change from academia to industry.
There is also a book by Matteo Tardelli called “The Salmon Leap for PhDs” which is all about things like self-assessment, opening up a LinkedIn account, thinking about your dream job, and whether that dream job actually exists.
“You don't have to fulfil all the requirements for a position, or highlight all of your publications.” Greg says. “List a couple of projects and highlight the project outcomes. That really shows how your skills helped you to publish the paper or to get around the obstacles along the way”
I ask more about being at Boeringher Ingelheim now and what the biggest learning curve has been.
“I think that the hardest thing was to adapt to a difference in publishing.” Greg considers.
Working at Boeringher Ingelheim is very dynamic and teamwork based, towards the goals of the company. This is quite different to a PhD that is quite personal goal focused, in terms of publishing the paper or the thesis.
He adds “Projects can also just stop because they are not worth the time, money and/or the effort for the company anymore”
He emphasises these areas are where those translational soft skills come in use.
Finally, I ask what his proudest moment has been?
Greg tells me that it was convincing his colleagues in the therapeutic areas that incorporating data driven insights to their drug target identification workflows can accelerate the target discovery process. He now has been invited to be part of several working groups in the therapeutic areas to help with data analytics right from the start of their projects. He recalls that it was his post-doc experience that really helped him with these skills: “you have to really make an effort in explaining complex concepts to people that are not used to those, or complex data visualisation approaches and so that was really key absolutely.”
