Diagnostic and prognostic prediction models predict an individual’s risk of having a disease, or experiencing a health-related event in the future. They are tools for medical decision making and patient counseling. While prediction models are flooding the scientific literature, very few get adopted in clinical practice. There is a large amount of “research waste” in this respect. We need more knowledge about the factors contributing to research waste or success in prediction modeling. With this knowledge, we can make prediction research more efficient.    

We are looking for a researcher to join a project researching the factors that influence the fate of prediction models. This project uses a mixed methods design: we use systematically collected data on published prediction studies, supplemented with qualitative follow-up data. The activities of the researcher will consist of:

• Systematic literature review on clinical prediction studies: screening and data extraction

• Tracking the fate of developed prediction models in a mixed-methods study

• Carefully logging all research actions

• Describing the results in scientific papers

We offer a 0.5 fte research position for 12 months. This could potentially be supplemented with additional teaching hours, if the researcher wishes. Remote working can be discussed.

The ideal candidate:

• Has a background in epidemiology, statistics or a comparable discipline;
• Has interest in and demonstrable good performance in statistical tasks;
• Is interested in qualitative research;
• Is interested in prediction modelling;
• Has 1-3 years post-Master research experience or a recent PhD degree;
• Is a diligent an structured worker;
• Has a good command of English, both written and spoken;
• Has good interpersonal skills;
• Is a team player;
• Has a pro-active and result-oriented attitude.

Fixed-term contract: 12 months.

The position is temporary for the duration of 12 months. Depending on experience and qualification, the gross monthly salary is scale 10 (max. € 4.402,-).

The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website www.maastrichtuniversity.nl > Support > UM employees.

Maastricht University

Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. Maastricht University has around 20,000 students and 4,400 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. The university hosts 6 faculties: Faculty of Health, Medicine and Life Sciences, Faculty of Law, School of Business and Economics, Faculty of Science and Engineering, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience.

Department of Epidemiology / School CAPHRI

The researcher will be stationed at the department of Epidemiology. She or he will be supervised by dr. L. Wynants.  The Department of Epidemiology’s mission is to improve human health and well-being through epidemiologic research and teaching. Its research aims to develop, improve and validate tools and strategies for etiology, prevention, diagnosis, treatment and care, and applying both observational and experimental designs. Its teaching focuses on epidemiology and epidemiological research methods, with the aim to enable students and professionals to apply scientific knowledge in their practice of public health and medicine.

CAPHRI

The researcher will be embedded in CAPHRI: Care and Public Health Research Institute. CAPHRI is one of Maastricht University’s Schools, with a focus on Healthcare Innovation and Public Health Research. CAPHRI aims to improve people’s health by performing the highest quality, multidisciplinary research across the complete healthcare chain, ranging from Prevention and Primary Care to Rehabilitation and Elderly Care.