Postdoc in Multimodal Stress Data & Analytics

Vrije Universiteit Amsterdam; Amsterdam; On-site; EUR 41,000 - 57,000; Part time

Benefits offered by this job

Holiday leave 232 hours/year

8% holiday allowance

8.3% end-of-year bonus

Contributing to commuting costs

Personalized benefits package

ABP pension

Job summary

Vrije Universiteit Amsterdam invites applications for a research-focused role within the Stress in Action consortium. You will develop data processing pipelines for multimodal datasets and help shape data governance and collection SOPs.

The position also supports teaching and supervision of B-thesis and M-thesis projects, linking research with hands-on student mentorship. You will advance your academic career by leveraging lab-based and ambulatory datasets, and you will contribute to scientific

Qualifications

• PhD in psychology, health sciences, neuroscience, biomedical sciences, epidemiology, bioinformatics, computer sciences, or related field (thesis defence candidates welcome).
• Affinity and experience with writing research papers.
• Experience with large-scale, multimodal datasets.
• Knowledge of basic psychometric principles and related statistics.
• Strong programming skills: Python, R, Matlab, or similar.

Responsibilities

• Develop and implement data processing pipelines for large-scale multimodal datasets.
• Contribute to team management and SOPs for data governance and collection (privacy, logistics, cross-cohort linkage).
• Support teaching activities including co-teaching Stress & Health and supervising B-thesis/M-thesis students.
• Run analyses and publish papers leveraging existing lab datasets and Stress in Action resources.

Skills

PhD required

Research writing

Multimodal data

Psychometrics

Python/R/Matlab

English skills

Communication skills

Student supervision

Dutch language

Education

PhD in relevant discipline

Job description

Vrije Universiteit Amsterdam invites applications for a research-focused role within the Stress in Action consortium. You will develop data processing pipelines for multimodal datasets and help shape data governance and collection SOPs.

The position also supports teaching and supervision of B-thesis and M-thesis projects, linking research with hands-on student mentorship. You will advance your academic career by leveraging lab-based and ambulatory datasets, and you will contribute to scientific