Do you want to make a challenging next step in your computational modeling research towards health care applications? Do you want to create impact by applying your research skills on multiscale modeling in the quickly growing health care demands of the aged population? Are you intrigued as we are for the possibility to study human resilience, brain aging and dementia from the paradigm of complexity sciences? Do you have an excellent track record in multiscale modeling that allows you to collaborate with technical physician researchers using sensor technology, and clinical researchers studying health problems of older patients?
In this case you are the person we want to offer a co-leading researcher position in the supervision of two ambitious research projects. The first project focuses on studying and modeling systemic resilience of older patients during hospital admission. The second project will focus on modeling dementia in old age as a complex disease in a multiscale model involving cellular mechanisms, and multi-morbidity, aging and environmental factors.
The candidate selected will be a postdoc candidate, well able to apply state of the art computational multiscale modeling techniques, as evidenced by his/her PhD research. The candidate is ambitious and passionate to aim for health and wellbeing improvement goals, by working on these projects, and by application (and additional training) of his/her (research) skills. He/she will also be eager to translate these new methods to other researchers and students via innovative computer simulation programmes. The professional will be appointed at the Department of Geriatrics, for 1.0 or 0.8 fte during a period of two years, with options for longer contracts depending on the success of ongoing and future grant applications.
What we offer:
Excellent research team with high level past performance in clinical research, epidemiology, and applied qualitative research. Tenure track possibilities depending on the candidate’s stage of career. Inspiring environment within a network of national and international top research groups. Participation in the Radboudumc Institute for Health Sciences and the Donders Research Institute for Cognitive and Medical NeuroSciences. Patient care environment with ongoing clinical research, including copromotorship in two PhD trajectories. Big scientific challenge at the cutting edge of currently available research methods, in an area with enormous societal impact because of our quickly aging societies.
- PhD degree in computer sciences, medical informatics, mathematics or physics
- Research experience in multiscale modeling which can be demonstrated by one or more of the following experience based skills:
- Competency in modelling complex data sets with mathematical or computational science methods (multiscale modelling, patient specific modelling, system dynamics modelling)
- Competent in applying multi-scale or time series modelling in human biology, fit to apply in studying human physiology
- Experience with analysis of wearable sensor based time series
- Competent in network analysis techniques connecting biological systems (eg different organs)
- The candidate should be capable to:
- Communicate and collaborate interdisciplinary to bridge the different scientific fields
- Flourish in a team of Dutch researchers, both culturally and intellectually
Tasks and Responsibilities
The researcher will:
- Translate modeling and empirical research methods based on complexity science/systems dynamics to the physiology and health of older patients
- Help to renew the field of geriatric research, which currently is dominated by static-measurements, with time series analyses and big data modelling techniques that together allow multiscale modeling
- Study tipping points in human disease trajectories, specifically in older adults
- Develop further research ideas and (co-)write grant applications for further translation of multiscale modeling/complexity science in geriatrics
- Develop an educational simulation model to teach the principles of multiscale modeling approaches to other disciplines