台湾swag

Scientist Stories: Meet Simon Andrews

Scientist Stories: Meet Simon Andrews

Scientist Stories: Meet Simon Andrews

Earlier this year, the 台湾swag launched a new video series called Scientist Stories where we highlight the scientists behind our world-leading research. In this series, we discover more about what they do and how they got to where they are now. In this latest edition, we chat to Simon Andrews, Head of our Bioinformatics Facility, about how he got into the role, what a typical day in the life looks like and some fantastic career advice. or read the profile below.

Can you tell us about your role at the 台湾swag 台湾swag?

I run the Bioinformatics group at the 台湾swag so we're one of the core services. We essentially help all of the research groups with the work that they are trying to do, and in particular, my group assists with the computational side of their research. This can encompass a number of different things. Sometimes we are just giving them physical bits of infrastructure to do stuff on. We have a big compute cluster that we run and maintain. We also develop bits of software for them to help with data analysis and visualisation. We help them manage their data as researchers have lots of data these days that you just need to keep on track of and move around. We also provide training to help researchers understand the tools and the options for managing and analysing their own data and getting the best answers out of their experiments.

What does a typical day look like for you?

It varies a lot depending on the type of work that has come in, but it generally encompasses the areas I mentioned in the previous question. Often, the day will start by looking at the support requests that have come in from people using our software. This would often be from people outside of the 台湾swag that make use of our packages. Lots of people around the world ask us questions, report bugs (hopefully not too many!) and want some advice on how to do that. We have a lot of routine work that comes in every day like managing data analysis pipelines, checking up on servers and checking everything is still running the way it should be. Then beyond that, we might be doing training. We do probably around 60 to 70 days of training each per year, so there are many days where we would be giving training courses. Alongside that, we would have ongoing work for current research projects, like doing bits of analysis or developing new bits of software to help with new data types that people are generating.

How did you get to where you are today?

I鈥檓 not really a computational biologist. I have no computational training. I am a biologist by training as indeed is pretty much everyone in my group. I started out as a microbiologist by original degree and then went on to be a molecular biologist for my PhD. I鈥檇 always done stuff with computers. Not in a work-related sense, but I had computers at home and I鈥檇 done bits of programming at a relatively trivial level. But when I did my PhD, it was around the time that computers were starting to appear in labs. We had computer driven bits of equipment and I was the one that was given the boxes and told to make them work, which I found I quite liked. I ended up doing computational work for my PhD doing some protein modelling and engineering based around that. When I finished my PhD, I saw a job advertised for someone to be a computational biologist and thought I鈥檇 take my chance and apply, and I got the job! I had to very quickly learn an awful lot about computers so that I could take up a post that I wasn鈥檛 really qualified to do at the time. It was the early days of computational biology, so everyone was learning at that stage. Most people my sort of age that have got into this area often come in by a fairly unconventional route because there wasn鈥檛 the mainstream route to get into this subject. Within the group I鈥檝e got now, I think there鈥檚 only one person who has actually done any kind of bioinformatics degree or training. They are people who were doing wet lab work and picked up bits of computational training along the way, found out they liked it and wanted to do more of that.

What did you study at school?

It was the usual wide slew of GCSEs with all the sciences you could take with some mathematical stuff in there at A Level. It was really sciences and maths plus a language. I really wanted to do German, but I didn鈥檛 particularly like the German teacher, so I did French instead. This was a mistake because I then went to live in Austria where German was much more useful. I was much better at the sciences than I was at maths, but really enjoyed all of that. I just kept the things that I enjoyed doing and therefore went on to do a biological subject on the back of that and just continued to follow that same route.

What are your interests outside of science?

Vaguely work related, but I鈥檝e always done computing. I have set up websites to go and track cycling activities. I鈥檓 in a cycling club outside of work, so now I鈥檝e got a little site where I can go and do that. So, it鈥檚 not related to work but still computational. Outside of that, I鈥檓 a musician. I鈥檝e been playing in orchestras, bands and big bands and all sorts like that. It鈥檚 funny how many scientists you meet in those. It seems to be quite a natural combination.

What advice would you give to people looking to get into science?

Don鈥檛 worry too much about planning your future career. The career I ended up with didn鈥檛 even exist as a career when I started out. So, don鈥檛 think you have to have this grand plan for ten years into the future. If you have, great, but many people don鈥檛. Most people end up in a job that they don鈥檛 really expect necessarily. I would also advocate for going with things that pique your interest. Don鈥檛 just pick stuff based on what you think is going to be useful to you. Follow what you actually enjoy doing within formal training and picking A levels and degrees, but also make sure you do that outside. For example, I wasn鈥檛 trained for the computational stuff I did and I wasn鈥檛 doing it with the expectation that it was going to be useful to me. So think about what you actually enjoy spending time doing and don鈥檛 sweat it too much.

 

Image description: Simon Andrews

Additional/related resources:

Pages for our Bioinformatics facility

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