Postdoc: Causal ML & RL for Health Innovations

Vrije Universisteit; Amsterdam; On-site; EUR 41,000 - 64,000; Full time

Job summary

Vrije Universiteit Amsterdam seeks a PostDoc at the intersection of machine learning and statistics to develop algorithmic improvements in causal inference and reinforcement learning, applying innovations to health data within Stress in Action and MINMED projects.

The role is embedded in the QDA group and collaborates with Amsterdam UMC, Erasmus MC and the University of Groningen. Expected to publish and contribute to teaching activities.

Qualifications

• PhD in ML and/or statistics with strong publication record.
• Experience in machine learning with health-related applications.
• Proficient in PyTorch and/or TensorFlow for research.
• Proven ability to work independently and in a team.

Responsibilities

• conduct research in ML and statistics and publish in top AI/ML conferences
• collaborate with the QDA group and partner institutions (VU/A'AM, Erasmus MC, Groningen)
• contribute to Stress in Action and MINMED projects and engage with partners
• participate in teaching activities and supervise Bachelor/Master students (20% time)

Skills

PhD in ML/Statistics

PyTorch

TensorFlow

Team collaboration

Education

PhD in ML or Statistics

Tools

PyTorch

TensorFlow

Job description

Vrije Universiteit Amsterdam seeks a PostDoc at the intersection of machine learning and statistics to develop algorithmic improvements in causal inference and reinforcement learning, applying innovations to health data within Stress in Action and MINMED projects.

The role is embedded in the QDA group and collaborates with Amsterdam UMC, Erasmus MC and the University of Groningen. Expected to publish and contribute to teaching activities.