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The employment is primarily dedicated towards carrying out the research as described below, with the aim to publish several academic articles in high-impact peer-reviewed journals. Due to the cross-departmental nature of the project, the PhD candidate will spend the first two years of employment at the Department of Methodology and Statistics and the last two years at the Department of Cognitive Neuroscience.
The position also involves contributions to teaching. The position and the environment in which the candidate will be embedded provide an optimal starting point for an academic career. The candidate will follow a customized track of graduate courses as part of the Interuniversity Graduate School of Psychometrics and Sociometrics (IPS) program which will further develop the candidate’s research skills and background knowledge.
Title: Prevention is Better Than Cure: Predicting the Onset of Postpartum Depression Using Early Warning Signals
It is estimated that 23,000 women suffer from postpartum depression in the Netherlands yearly, making it the most common psychiatric disorder among new mothers. Luckily, research suggests that many mothers respond well to early intervention. In fact, intervening in time can even prevent an onset. However, research has shown that a depressive episode is highly heterogeneous: Every mother experiences her own form of postpartum depression, caused by her own set of causes (a different network of symptoms and risk factors). Consequently, the optimal timing and type of prevention also differ between mothers.
This project focuses on developing and applying advanced statistical methods to improve the timely identification (and with that, the prevention) of postpartum depression. This includes (1) the identification of causal predictors using secondary data, (2) applying a network approach to construct individual networks of symptoms and risk factors, and (3) training and validating a deep learning algorithm for early warning signals of an episode.
As a collaboration between the Department of Methodology and Statistics, Cognitive Neuroscience and Tranzo, this project is highly multidisciplinary, as will be the tasks of the PhD candidate: Managing the collection of ESM data, applying (and developing) advanced statistical analyses (such as Bayesian networks and machine learning algorithms) and consulting with clinical practitioners. The ideal candidate does have a solid background and interest in both statistical methods as well as clinical psychology (psychopathology).
• Have a (research) MSc. in a relevant area such as (Applied) Statistics, Data, Science, Artificial Intelligence, Cognitive Science, Computer Science, Cognitive Psychology or a related discipline;
• Strong programming skills in R, Matlab, and/or Python or otherwise;
• Have a strong interest in clinical psychology (psychopathology) and/or health research
• An ideal candidate has experience in developing and/or applying advanced statistical methods, experience in the collection and analysis of Intensive Longitudinal Data (ILD) and demonstrable interest (for example in the form of a minor or extra courses) in the field of clinical psychology. However, any candidate that shows a demonstrable interest in analytical as well as empirical work on the project’s topic will be considered.
• Be enthusiastic about collaborating and participating in groups of academic and non-academic partners;
• Possess good communication skills and be an efficient team worker;
• Be fluent in English, both spoken and written.
Conditions of Employment
Tilburg University is among the top Dutch employers and has an excellent policy concerning terms of employment. The collective employment terms and conditions for Dutch universities will apply. Initially the appointment will be on a temporary basis for the period of 1 year. After a positive first year evaluation the contract will be prolonged for 3 years.
The salary for the position of PhD-candidate on a full-time basis ranges between € 2541,- and € 3247,- gross per month (not included are various allowances).
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