Georgios went on to PhD studies at one of Europe’s highest ranked universities
Georgios Iatropoulos graduated from the master’s programme in Engineering Physics (Biomedical Physics track) in 2015. He is now a PhD student at EPFL in Switzerland.
Hi Georgios, what are you working with at the moment?
I’m a PhD student enrolled in the neuroscience doctoral programme at EPFL in Switzerland. More specifically, the field I’m working in is called computational neuroscience (sometimes also called theoretical neuroscience or simulation neuroscience). This is a very interdisciplinary field of research that uses knowledge from computer science, theoretical physics, maths, and neurobiology to develop mathematical models of the nervous system. Ultimately, the aim is to understand how the human brain functions and why it is constructed the way it is. The project I’m working on deals with the mathematical modelling of a neurobiological phenomenon called synaptic plasticity. Synapses are connections between neurons that allow neurons to transmit electrical signals to each other, and the term synaptic plasticity refers to the changes that occur in these connections whenever we learn new things or form new memories. Knowing what causes synapses to be created, strengthened, weakened or removed is essential in order to understand how learning occurs in our brains under normal conditions, as well as how our learning ability develops during childhood and how it is affected by various diseases, such as Alzheimer’s disease.
What can a regular day look like at your job?
In general, I spend most of my time working on ways to solve whichever mathematical problems emerge from the research question I’m trying to answer at the moment. In practice, this typically means first creating a conceptual model of how a certain cognitive or neurobiological process (memory and synaptic plasticity in my case) might be implemented in a circuit of biological neurons. Afterwards, I work on developing a set of mathematical equations to calculate the electrical and chemical activity inside a synapse, a single neuron, or a circuit of neurons, in order to describe in detail the process I wish to understand. Finally, these mathematical models tend to be quite complex and are therefore often simulated on a computer (or a supercomputer in the most demanding cases). In this way, the mathematical model of a single neuron or an entire brain region can be tested under various physiological conditions and with different stimuli to see how useful it is in explaining observations done in real biological experiments.
Whenever progress is made and interesting results are produced, a substantial amount of time is then spent writing an article that summarizes all the work so it can be published in a scientific journal and shared with the rest of the scientific community.
In parallel to this work, I divide my time between reading recently published research articles, working as a teaching assistant, and taking courses. Once or twice every year I might also travel to a conference in order to present recent results and meet other neuroscientists.
Have you worked with anything else since you graduated?
Yes and no. Between graduation and the start of my PhD at EPFL, I worked for a couple of years as a research assistant at the Gösta Ekman Laboratory at Stockholm University, in collaboration with the Computational Brain Science Laboratory at KTH. I worked on a computational neuroscience project that dealt with modelling the brain’s odour memory system. Therefore, technically, I had a job before my PhD but it was still academic research within the same field.
Why did you choose this programme at KTH?
Before going to university, the topics that always interested me the most in school were physics, math, and programming. By the time I had to choose a university programme, towards the end of high school, I had become interested in trying to pursue a career in research and technological development, either in academia of in the industry. The five-year engineering programme at KTH was therefore a natural choice. The reason why I ultimately chose Engineering Physics was due to the wide scope and high level of the curriculum. It is demanding but gives students a solid academic foundation by introducing them to a very diverse range of topics within physics, math, and computer science, which later enables them to take a wide variety of master programmes, depending on what type of field they wish to work in. The result is that graduates of the Engineering Physics programme can be found working in businesses involved in everything from IT and software development to heavy industry as well as finance and management consulting. A large fraction of the students pursue academic research within a wide range of STEM fields, such as physics (theoretical and applied), computer science and machine learning, biotechnology and biomedical engineering, as well as mathematics and financial modelling.
In my case, I was exposed to computational neuroscience early on in the programme and became very fascinated by the idea of using physics and computer science to describe and understand the mechanisms behind human cognition. I therefore decided to take the Biomedical Physics track within the Engineering Physics master’s programme and to write my master’s thesis on a subject within computational neuroscience. After that, I wanted to continue working in the field and decided to pursue a PhD.
Is there any insight or knowledge you acquired during your studies that has been extra useful for you in your career?
In general, a math-and-physics heavy education like the Engineering Physics programme instils in you an independent work ethic as well as an ability to solve a variety of complex scientific and technological problems by allowing you to see how they can be divided into simpler problems, each of which can be tackled by the mathematical tools at your disposal. Honing such analytical skills is of course essential to carry out scientific research.
What were the best aspects of your studies at KTH?
During my studies, I did a couple of lab internships and worked as an organiser of career fairs and various corporate events. These opportunities to explore a wider network of university life and learn more about the cutting edge in different scientific fields and within various tech companies were very enjoyable.
What are your plans for the future?
To continue working on my research and complete my PhD studies. What will happen after that is a bit more difficult to say. There are many interesting opportunities to do neuroscience-related R&D (regarding for example neurotechnology and artificial intelligence) both in industry and academia nowadays.
What would you want to say to a student thinking of applying to this programme?
As mentioned earlier, the undergraduate years of the Engineering Physics programme are spent giving students a very robust foundation in math and physics, and most of the courses early in the programme are more theoretical in nature. This can be very demanding, but the pay-off is that students later are able to choose a specialization from a very large selection of master’s programmes. Moreover, the curriculum is good preparation for students who aim to take doctoral studies later on and pursue an academic career, which is also why many of the Engineering Physics students tend to be interested in some form of research and development. In conclusion, I would say that this programme is good for students who are interested in studying maths, physics, computer science, and technology at an advanced academic level, and who might be interested in continuing on to a PhD programme.