PhD Position in Computational Biology: Using Machine Learning to Understand the Immune System

Are you an aspiring data science researcher with an interest in human immunology, causal inference in dynamical systems, and/or computer vision? Would you like to apply AI and machine learning for fundamental research in biology? Then you have a part to play as a PhD candidate. By combining simulations and machine learning, you will help us develop new, innovative methods to extract knowledge from immune cell movement videos.

When thinking of cells, most people imagine static building blocks. Yet many processes in health and disease critically rely on cell movement. A key example is the defence against viruses and cancer: the cells of our immune system are strikingly motile as they navigate the maze of tissues in the human body, interact and communicate with other cells, search for signs of anomalies, and swarm to sites of infection.

Specialised microscopes allow biologists to film these processes, yielding videos that are rich in information but limited in the amount of (annotated) data for any given application. As a result, many existing AI techniques are not directly applicable to new datasets, making it very difficult to decode these videos and zoom in on the where, when, and how of key events in the data.

Our group aims to overcome these hurdles to extract meaningful insights from videos of cells. We do this by integrating data science, statistics, and AI with (bio)physics-based simulation models – using simulations to build better AI or using AI to build better simulations. In your project, you will master the arts of simulation and machine learning to help us achieve this goal.

You will be part of a larger team, for which there are currently two open positions. One PhD project will focus specifically on cell movement as a time series, developing causal inference methods for cell dynamics. The other project will be broader and, depending on your preference and developments in the field, it may focus more on the time series aspect or the computer vision aspect of video analysis. For both projects, you will first become proficient in state-of-the-art methods in the field and then improve these by integrating them with physics-based simulations.

You will spend roughly ten percent of your time (0.1 FTE) assisting with teaching activities in our department. You may, for example, be asked to provide tutorials , grade coursework, deliver presentations during classes, or supervise student projects.

We are looking for two PhD-candidates.

Requirements:

• You should hold a Master’s degree in Computer Science, Life Sciences, or another relevant discipline. You might, for example, be a biologist with experience in simulation modelling and/or machine learning, or a data scientist with a strong interest in biological applications.
• You have experience with data science and machine learning or the analysis and/or simulation of biological data, or a combination thereof.
• You are eager to learn more about any of the above-mentioned topics that you are less familiar with.
• You are able to communicate clearly about complex topics, allowing you to work in an interdisciplinary setting.

Salary Benefits:

• We will give you a temporary employment contract (1.0 FTE 4- year contract) of 1,5 years, after which your performance will be evaluated. If the evaluation is positive, your contract will be extended by 2.5 years (4-year contract).
• You will receive a starting salary of €2,770 gross per month based on a 38-hour working week, which will increase to €3,539 from the fourth year onwards (salary scale P).
• You will receive an 8% holiday allowance and an 8,3% end-of-year bonus.
• You will be able to use our Dual Career and Family Support Service. The Dual Career Programme assists your partner via support, tools, and resources to improve their chances of independently finding employment in the Netherlands. Our Family Support Service helps you and your partner feel welcome and at home by providing customised assistance in navigating local facilities, schools, and amenities. Also take a look at our support for international staff page to discover all our services for international employees.
• You will receive extra days off. With full-time employment, you can choose between 30 or 41 days of annual leave instead of the statutory 20.

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

3.8 hours per week

Houtlaan 4