As a post-doctoral researcher at the Groningen Research Institute of Pharmacy I applied novel methodologies to big data in a pharmaceutical and epidemiological context. I also teach statistics to pharmacy students and supervise master and PhD students.

I was accepted for a PhD position at the Interdisciplinary Centre for Psychiatric Epidemiology (part of the UCP, UMCG), starting on the first of februari. The main goal is to develop and use statistical methods to research depression. The models I will be looking at are network based. Network models have been used with success in areas such as systems biology and computer imaging. It is my intention to adapt and use these methods such that subtypes of depression within large datasets can be found.

As a side job I was a statistical consultant in the department of psychiatry at the UMCG, where I helped colleagues with statistical and computational problems. Specific projects undertaken included writing a tutorial on regularized vector autoregressive models, creating a Shiny app for investigating the effect of data pruning on autocorrelation effects in time series data and figuring out how to perform linear regression on periodic data using the Cosinor-method.

Data scientist/technical consultant at www.bebr.nl.

I visited the University of Calgary where I did research and wrote two papers with prof. dr. Patten. The first paper concerns differences in depression symptomatology between a sample of multiple sclerosis patients and a general population sample and uses a regularized vector autoregression model to estimate longitudinal networks for these groups. The second paper is about investigating the use of a data driven clustering method to try to find evidence-based subtypes of depression, along with semi-parametric network models.

Help students with difficulties while solving problems, grade exams and homeworksets.