Postdoctoral fellowship in machine learning for next-generation biomedicine

Key Skills

Python Programming, Machine learning techniques, AI technology, R Programming, Statistics, Statistical modeling

Job Description

This is an opportunity to work on advanced machine learning methodology for complex scientific questions at one of Germany's flagship biomedical institutions. The position is within in the Mukherjee Group, which focuses on machine learning methodology for next-generation biomedicine. Current focus areas include deep causal learning, high-dimensional problems and scientifically-interpretable modelling, with applications in large-scale molecular biology and omics as well as deep phenotyping.

We are looking for highly qualified candidates in machine learning, AI or statistics, with an interest in methodological research, motivated by, and applied to, large-scale biomedical data. We are particularly interested in candidates with strong methodological expertise in one or more of causality, deep neural networks and high-dimensional methods. Prior experience in biomedical research is not required. The working language is English and knowledge of German is not required.

Requirements

Candidates (f/m/x) should have, or shortly expect to receive, a PhD in machine learning, statistics, computer science, applied mathematics (or related fields) with a strong background in machine learning or computational statistics. A solid background in machine learning and statistical fundamentals and strong ML/statistical computing skills (in one or more of Python, R, etc.) are important.

We offer

• Excellent scientific infrastructure and state of the art techniques
• An international environment characterized by a strong focus on science and research
• Working in an international team within a stimulating research environment and very well-equipped laboratories
•  A high potential for the individual development of our employees (including targeted personnel development)
• A full-time position, initially temporary limited to 2 years, with possible extension
• Employment, payment and social benefits are determined by the Public Sector Collective Agreement (Tarifvertrag für den öffentlichen Dienst – TVöD Bund)