Marjolein Fokkema
Closing soon
2 weeks ago
PhD position in machine learning for scientific inference for behavioural science Leiden University in Netherlands
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Mar 13, 2026
Country
Netherlands
University
Leiden University

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Where to contact
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About this position
This PhD position at Leiden University offers an exciting opportunity to advance machine learning for scientific inference within behavioural science. The project, led by Dr. Marjolein Fokkema and funded by the Dutch Research Council (NWO), focuses on developing new statistical methods that produce valid, generalizable, and interpretable effect sizes with accurate uncertainty estimates. You will also contribute to ML-based meta-analysis, enabling comparison and combination of results across studies.
As a PhD candidate, you will work at the intersection of statistics, machine learning, and behavioural science. Your tasks include developing and implementing statistical methods in open-source software, conducting simulation studies, applying methods to real-world behavioural science data, publishing in scientific journals, and presenting at conferences. Collaboration with researchers from behavioural science and related fields is encouraged, as is facilitating applications through methodological or software improvements and documentation.
You will join the Methodology and Statistics Unit within the Faculty of Social and Behavioural Sciences, a dynamic environment with a strong focus on Neuroimaging Statistics, Statistical Learning and Artificial Intelligence, Applied Psychometric and Sociometric Modelling, and Responsible Research Methods. The faculty is home to approximately 7,000 students and 1,000 staff members, and the Institute of Psychology alone comprises about 5,000 students and 600 staff. The team values scientific integrity, open science, and inclusiveness, providing a supportive and international work environment.
Applicants must have a completed (research) master's degree in statistics, data science, psychology, or a related quantitative field. Required skills include strong programming in R, experience with data analysis and Monte Carlo simulation studies, and proficiency in English. Desirable skills include background in Bayesian regression, interpretable machine learning, meta-analytic techniques, and experience in developing statistical methods or software.
The position offers a full-time employment contract (38 hours/week), initially for one year with possible extension for three years after positive evaluation. The salary ranges from €3059 to €3881 gross per month, with additional benefits such as holiday allowance, end-of-year bonus, pension scheme, reimbursement of commuting costs, flexible working hours, minimum 29 leave days, options for sabbatical or paid parental leave, sports subscription and bicycle scheme, hybrid working, home-working allowance, and provision of a laptop and mobile telephone.
Applications are accepted until March 13, 2026. Interviews will be held March 14-24, 2026, and the project starts April 16, 2026. For more information or questions, contact Dr. Marjolein Fokkema at [email protected]. For details on employment conditions and application procedures, visit the university's job application page. Leiden University is committed to promoting an inclusive community where diversity in experiences and perspectives enriches teaching and research.
Apply online via the provided link with your resume and motivation letter. The university values mobility and inclusiveness, and a pre-employment screening may be part of the selection procedure.
Funding details
Available
What's required
Applicants must have a completed (research) master's degree in statistics, data science, psychology, or a related quantitative field. Strong programming skills in R, experience with data analysis and Monte Carlo simulation studies, and strong written and spoken English are required. Clear communication skills and a genuine interest in behavioural science, demonstrated by relevant coursework, projects, or extracurricular activities, are expected. Desirable but not required are background in Bayesian regression, interpretable machine learning, meta-analytic techniques, and experience in developing statistical methods or software.
How to apply
Apply online via the application link by March 13, 2026. Submit your resume and motivation letter. For questions, contact Dr. Marjolein Fokkema at [email protected]. Interviews will be held March 14-24, 2026.
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