Postdoctoral Researcher (Quantitative Psychology/Data Science in Psychology)

For our Division of Cancer Survivorship & Psychological Resilience at the DKFZ Hector Cancer Institute at the University Medical Centre Mannheim (UMM), we are looking for an outstanding and highly motivated 

Postdoctoral Researcher (Quantitative Psychology/Data Science in Psychology). 

The successful candidate will use advanced quantitative methods to contribute to innovations in modelling psychological resilience among cancer survivors and populations at risk.

The DKFZ Hector Cancer Institute at the University Medicine Mannheim (UMM) was established in 2019 in the frame of a partnership between the German Cancer Research Centre (DKFZ) in Heidelberg, the University Medical Centre Mannheim, and the Medical Faculty Mannheim of Heidelberg University with generous support from the Hector Foundation II. The aim is to carry out excellent translational cancer research in the fields of precision oncology, cancer prevention, early detection, and survivorship.

Our newly established Division for Cancer Survivorship & Psychological Resilience within the DKFZ Hector Cancer Institute is dedicated to the identification of neuropsychological resilience mechanisms in the general population and cancer survivors and to develop effective and innovative prevention and intervention measures to strengthen mental health particularly in cancer patients. We combine experimental neuropsychological methods and large-scale cohort studies to advance mechanistic resilience research in the field of cancer survivorship. 

Your Tasks:

• Design and lead method development and statistical modelling in resilience assessment (e.g., dynamic/latent-variable models, Bayesian hierarchical models, causal inference, time-series analysis, cognitive modelling).
• Build robust, reproducible data handling and analysis workflows in R and/or Python; author reusable packages and pipelines.
• Collaborate across DKFZ programs; co-supervise students; contribute to grant applications.
• Publish in high-impact journals and present at international conferences.
• Provide workshops and training for the research team in new analytic approaches
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• Your Profile:
• Applicants must hold a PhD degree in quantitative psychology, psychological methods, cognitive science, data science, applied statistics, psychometrics or a related field.
• We invite applications from individuals with a strong quantitative background, extensive experience with scientific coding in R and/or Python, and prior experience in applying quantitative methods and modelling to real-world questions in domains such as clinical or health psychology.
• Excellent communication and organizational skills and proficiency in English are mandatory. Proficiency in German is desirable.
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• We offer:
• Excellent framework conditions: state-of-the-art equipment and opportunities for international networking at the highest level.
• Remuneration according to TV-L incl. company pension scheme and capital-forming benefits.
• 30 days of vacation per year.
• Flexible working hours.
• Possibility of part-time work.
• Family-friendly working environment.
• Sustainable travel to work: subsidized Germany job ticket.
• Our Corporate Health Management Program offers a holistic approach to your well-being.
• Develop your full potential: access to the DKFZ International Postdoc Program and DKFZ Career Service with targeted offers for your personal development to further develop your talents.
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• Interested candidates should submit the following documents as a single PDF file ONLY via our online application tool (https://jobs.dkfz.de/en/jobs/168268/form):
• Cover letter (1–2 pages) outlining your fit
• CV with publications and links to code/software (if available)
• Up to 3 representative papers or preprints (methods and/or applied)
• Contact details of 2–3 academic referees
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Contact_: Prof. Dr. Michèle Wessa
Phone: +49 6221 42 4806

The position is initially limited to 3 years, with the possibility of extension. The position can be filled immediately. Application deadline is January 12th, 2026.