Specialisation Data Science for Health

Are you interested in playing with data and analysing the enormous amount of data that are collected on nutrition and health? Will you device new methods to collect these data? Will you build a model out of the chaotic data around us?

The purpose of Data Science for Health is to find patterns in a multitude of data and from these data formulate new hypotheses on how nutrition and nutrition behaviour influence our health. You will become a nutrition & health researcher with the specific knowledge and skills needed to collect, analyse, visualise and extract actionable knowledge from big data.

The current standard way to collect data on food intake is to interview people who have joined e.g. an intervention study. But nowadays we can also use autonomous data collection (e.g. by smart watches that keep track of every bite you take or by using hyperspectral cameras that, we hope, will analyse the nutrient composition of the food we eat).

Watch the video on Data Science at WUR here (sound is in English, duration 2:05)

In this specialisation the research is data-driven as opposed to hypothesis-driven. You work with algorithms but you might also come up with new algorithms. Data-driven research does not mean you are only logging your data. You’ll have to read a lot about your research field to be able to combine the relevant data. Visualising your results and working together with other researchers also makes up an important part of your work. After all we want to use gained insights in the field of nutrition and health.

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Study programme

In the first year you combine compulsory courses (like Data Science for Health: principles and Exposure assessment in Nutrition and Health research) with restricted courses (such as Data Types for Innovative Measurements in Health and Nutrition and Data Types in Food and Consumer Behaviour and Artificial iIntelligence for Food and Health). There’s also space to choose your own preferred courses. You finalise your first year with Data Science Ethics.

The second year is for your thesis and internship. You do your thesis with one of the chairgroups in our university working on Data Science for Health. For your internship you go to a company or other organisation outside the university. And there’s still room to follow e.g. Solving Societal Health Challenges with Data science. In this course you participate in a team to advise an actual company or organisation on a problem in the health domain. You bring together academic insights and practical knowledge and come up with an advice on future actions for that company.

You will find more information on timetables, courses and course content of this specialisation in the study handbook.