Postdoc: Multimodal Data Pipelines for Stress Research

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

Benefits offered by this job

Salary €3,706–€5,103 gross per month (

0.8–1.0 FTE contract

Holiday allowance and end-of-yearbonus

Job summary

Vrije Universiteit Amsterdam invites applications for a research-focused role in the Stress in Action cohort enrichment study. You will develop data processing pipelines for multimodal data, contribute to governance SOPs, and support teaching and supervision of students.

The role advances an academic career with access to rich lab and ambulatory datasets. Strong candidates have a PhD in a related field, experience with large datasets, and programming skills in Python, R or MATLAB.

Qualifications

• PhD required in a relevant field (psychology, health sciences, neuroscience, biomedical sciences, epidemiology, bioinformatics, computer sciences, or related).
• Experience with writing research papers and with large-scale multimodal datasets.
• Knowledge of basic psychometric principles and related statistical methods.
• Strong programming skills in Python, R, MATLAB or similar.
• Fluent in English; Dutch language skills are a strong asset.

Responsibilities

• Develop and implement data processing pipelines for large multimodal datasets.
• Contribute to team management and SOP development for data governance and collection.
• Support teaching activities and supervise students in research projects.

Skills

Affinity for writing papers

Experience with large-scale multimodal

Statistical methodology knowledge

English writing and presentation

Communication and social skills

Supervision of students

Dutch language skills (asset)

Education

PhD in psychology/health sciences/neuroscience/biomedical sciences/epidemiology/bioinformatics/computer science

Tools

Python

R

MATLAB

Job description

Vrije Universiteit Amsterdam invites applications for a research-focused role in the Stress in Action cohort enrichment study. You will develop data processing pipelines for multimodal data, contribute to governance SOPs, and support teaching and supervision of students.

The role advances an academic career with access to rich lab and ambulatory datasets. Strong candidates have a PhD in a related field, experience with large datasets, and programming skills in Python, R or MATLAB.