项目介绍

2025年4月23日

The psychological literature on network modeling is growing rapidly, and Bayesian statistics offers concrete solutions to outstanding methodological problems (e.g., Marsman, & Rhemtulla, 2022). The PhD student will develop new network models for longitudinal psychological data, Bayesian methods to analyze the new models, and implement the newly developed methods in open statistical software (i.e., R, C++, and JASP). In addition, the candidate will work on eliciting meaningful prior distributions for network structures and parameters based on prior research, collaborate with substantive researchers who wish to apply the new methodology to their existing datasets, and work with the Bayesian Graphical Modeling Lab to disseminate the new methodology through review, guideline, and tutorial papers (e.g., Huth, et al., 2023; Sekulovski et al., 2024; van Doorn, et al, 2021) and workshops (e.g., the Psychological Networks Amsterdam Summer and Winter Schools).

What are you going to do

You will:

• conduct PhD research in Bayesian methodology for network analysis (i.e., derive new models, develop Bayesian methods for their analysis, and implement these developments in software);
• regularly present research results at (international) workshops and conferences, and publish them in international journals;
• complete academic work leading to a PhD thesis to be defended at the Faculty of Social and Behavioral Sciences of the University of Amsterdam with the aim of obtaining a PhD;
• make Amsterdam (or a location within commuting distance) your primary residence for the duration of the PhD project.

What do you have to offer

For this position, it is essential that you have:

• a Master’s, Research Master’s, or equivalent degree with specialization in psychological methods, psychometrics, statistics, or a related discipline. The degree must be completed by the start of your employment;
• a serious interest in mathematical or computational statistics;
• excellent verbal and written communication skills in English;
• excellent programming skills in R;
• excellent interpersonal and organizational skills;
• experience with Bayesian methods.

It is also essential that you make Amsterdam (or a location within commuting distance) your primary residence for the duration of the PhD project.

It is also desirable (but not essential) that you have

• programming experience in C, C++, or JASP;
• experience with network- and longitudinal or time-series models;
• experience with computational statistical methods, especially Markov chain Monte Carlo methods.

Please note that knowledge of the Dutch language is not required for this position, nor is it required for being able to live in Amsterdam.

What else do we offer

• a position in which initiative and input are highly valued;
• an enthusiastic and warm team that is open to new colleagues;
• an inspiring academic and international working environment in the heart of Amsterdam.