Post‑doctoral Assistant in Data Analysis & Mathematical Modelling

About the role

The BioML research group seeks a post‑doctoral researcher to advance machine‑learning methods for life‑science data. The position combines high‑level research with teaching and supervision duties.

Key responsibilities

• Conduct academic research (≈70% of time) on machine‑learning topics such as multi‑target prediction, sequence learning, time‑series analysis, uncertainty quantification and probabilistic models, focusing on omics data.
• Teach at Master’s level, serve as the main lecturer for the course “Introduction to Data Science”.
• Supervise Bachelor dissertations, Master dissertations and co‑supervise doctoral projects.
• Actively contribute to securing competitive research funding.

Required profile

• Doctoral degree in computer science, applied mathematics, physics, bioscience engineering, or a related field (must be obtained before start).
• Demonstrated research experience in machine learning and a strong publication record.
• Interest and ability to coach Bachelor, Master and doctoral students.

Required skills

• Machine‑learning methods for life‑science applications.
• Multi‑target prediction, sequence learning, time‑series analysis.
• Uncertainty quantification and probabilistic modelling.
• Analysis of genomics, transcriptomics, proteomics (omics) data.

What we offer

• Fixed‑term appointment of 3 years, with a possible second term of up to 3 years.
• Salary according to the AAP5 scale, with standard university benefits (training opportunities, 36 days paid leave, bicycle commuting reimbursement, eco‑cheques, etc.).