The PhD candidate will develop and apply dynamic models of human metabolic physiology to develop ‘Digital Twins’ of patients with diabetes. Digital twins are virtual copies of human metabolic physiology that enable simulations based on data collected from the patient and artificial intelligence. The models are expected to perform realistic simulation of glucose and insulin dynamics in response to the intake of food, the effect of medication, physical activity and mental stress and should allow for large differences between individuals.
The PhD position is part of the NWO funded project 'DiaGame: serious and personalized game for self-management of diabetes.' The DiaGame project applies learning systems and biomedical simulations to develop a data-driven, personalized serious game that empowers individuals with diabetes to manage the disease they are facing. In order to personalize the game, we will integrate our expertise on processing of personal data collected from health-related smartphone apps into our game platform. The information that this approach yields will be used to personalize the simulation that drives the game. Together, this will allow the use of patient-gathered health data to make the diabetes game a realistic representation of the condition of the gamer. Hence, the goal is to obtain a personalized simulator for a person's metabolism. In this way, DiaGame will change the approach to diabetes care by using data sciences in support of a data-driven personal diabetes games for learning to manage their own disease. Ultimately, this will improve the quality of life for patients and lighten the socio-economic and medical burden that diabetes has. The partners in the project include the Department of Industrial Engineering & Innovation Sciences of TU/e and Maxima Medical Centre in Eindhoven.
Tasks and responsibilities
The PhD candidate is expected to:
We are looking for high-level candidates with an MSc degree in engineering and life sciences (biomedical engineering, biotechnology, bioengineering) with specialization in computational modelling, computational biology, or equivalent. She or he should be interested in quantitative methods, modelling and data integration with affinity for human metabolism and its regulation.
The candidates should have:
More information can be obtained from:
Please upload your application with extended curriculum vitae.