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# Job offer

- **Company:** EURAXESS
- **Location:** Nuthetal, Germany
- **Contract:** Temporary contract
- **Skills:** Python (Programming Language), Machine Learning, Reinforcement Learning, Multimodal Learning, Deep Learning, Free and Open-Source Software, Programming Languages
- **Published:** October 3, 2026
- **Apply:** https://euraxess.ec.europa.eu/jobs/403131#where-to-apply

## About the Role

* Excellent master and doctoral degree with demonstrated expertise in Deep Learning / Multimodal Learning / Reinforcement Learning
 * Publication record at top machine learning conferences
 * Expertise in programming languages such as R or Python
 * Experience with advanced deep learning frameworks & open-source software development
 * Strong communication skills and ability to work in interdisciplinary teams, PhD or equivalent, * Excellent master and doctoral degree with demonstrated expertise in Deep Learning / Multimodal Learning / Reinforcement Learning
 * Publication record at top machine learning conferences
 * Expertise in programming languages such as R or Python
 * Experience with advanced deep learning frameworks & open-source software development
 * Strong communication skills and ability to work in interdisciplinary teams

Languages
ENGLISH

## Description

* Develop, implement and apply digital twins and RL agents based on multimodal health data for personalized recommendations of dietary and other health behavior to improve health
 * Collaborate with causal inference researchers to jointly develop methods for analyzing multimodal digital N-of-1 trials (patient reported outcomes, wearables, images, audio, omics data) linking causal inference and deep learning
 * Develop methodology for individual-level inference of large epidemiological studies (e.g., EPIC Potsdam study, German National Cohort study) including omics data
 * Implement the developed models for multimodal studies run on the StudyU platform with collaborators in Germany, Australia, USA, South Korea and Ghana
 * Develop clear data visualizations, reports, and written summaries to communicate results - for scientific publications but also for study participants and patients
 * Collaborate with clinicians, epidemiologists, software developers and laboratory scientists in the design of new studies and analysis of existing data


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