Postdoctoral Researcher In Multimodal Human Sensing And Advanced Behavioral Data Analysis
EPFL - EPF Lausanne
Lausanne, Switzerland
Not specified; not specified; not specified
On-site
Python or r programming skills
Multimodal physiological signal processing
Advanced statistical modeling expertise
The position involves leading the technical core of an SNSF-funded project investigating human motivation and stress responsiveness using immersive virtual reality
Job Summary
The position involves leading the technical core of an SNSF-funded project investigating human motivation and stress responsiveness using immersive virtual reality.
Responsibilities include developing robust pipelines for acquiring, synchronizing, and analyzing complex multimodal data streams from physiological sensors and motion tracking.
Candidates will collaborate with a multidisciplinary team at EPFL's Laboratory of Behavioral Genetics to validate behavioral assays and contribute to high-impact scientific publications.
Matching Summary
The position involves leading the technical core of an SNSF-funded project investigating human motivation and stress responsiveness using immersive virtual reality.
Salary
Not specified; Not specified; Not specified
Skills & Requirements
Must-have
Python or R programming skills
Multimodal physiological signal processing
Advanced statistical modeling expertise
Experimental system troubleshooting
Data synchronization and quality control
Nice-to-have
Unity game engine development experience
Virtual reality experimental setup knowledge
Biopac physiological acquisition systems
Bayesian hierarchical modeling background
Open science and reproducible pipelines
Key Requirements
PhD in biomedical engineering, computer science, or related quantitative field
Strong quantitative and statistical reasoning capabilities
Experience with time-series and sensor-based data analysis