Leibniz Association 
Potsdam-Rehbrücke, Germany Resumen de la oferta
The German Institute of Human Nutrition (DIfE) in Potsdam-Rehbrücke, part of the Leibniz Association, invites a Postdoc (m/f/d) to join its new Department of Computational Precision Nutrition. The role focuses on Deep Learning and Reinforcement Learning applied to multimodal biomedical data, including digital N‑of‑1 trials and large epidemiological studies. Responsibilities include developing digital twins, RL agents, causal‑inference methods, and data visualisations, and collaborating with clinicians, epidemiologists, and software developers. Candidates should hold a master’s or PhD with strong DL/ML experience, programming skills in R/Python, and a publication record in top ML conferences. The position offers a 3‑year contract, TV‑L level 13 salary, pension, 30 days vacation, and a supportive, interdisciplinary environment near Berlin.
Generado a partir del contenido almacenado de la oferta. Confirma siempre los detalles en la publicación oficial.
Descripción del proyecto
The German Institute of Human Nutrition Potsdam-Rehbruecke(DIfE) is a member of the Leibniz Association. The institute’s mission is to conduct experimental and clinical research in the field of nutrition and health, with the aim of understanding the molecular basis of nutrition-dependent diseases, and of developing new strategies for treatment and prevention.
The newly established Department of Computational Precision Nutrition (CPN) invites applications for
1 Postdoc (m/f/d) in Deep Learning / Reinforcement Learning
starting as soon as possible.
The Department of Computational Precision Nutrition develops methods and software for the analysis of both population-level and individual-level data, to enable personalized health recommendations based on dietary patterns, behaviors, and diet-associated biomarkers. We aim to contribute to the personalized prevention and treatment of chronic diseases and advance our understanding of the mechanisms underlying their development. Two methodological focus areas are digital N-of-1 trials and deep learning-based modeling of multimodal biomedical data.
We are seeking one highly motivated scientist with expertise in Deep Learning / Reinforcement Learning to join our team.
Tasks include
- 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
Skills and requirements
- 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
We offer
- Opportunity to develop your own research profile among the exciting research topics described above
- A dynamic, international and interdisciplinary research environment as well as excellent working conditions and outstanding technical equipment
- Employment with remuneration according to TV-L, level 13, plus annual special payment and company pension scheme
- Family-friendly working conditions (certificate “audit berufundfamilie”)
- Supporting of mobility with a jobticket for using the public transport
- Location close to the vibrant city of Berlin, with easy accessibility by public transport or car
- 30 days of vacation
- Participation in the benefits program for employees („Corporate Benefits“)
The advertised position is available for initially 3 years.
We promote the employment of people with severe disabilities and are committed to equal opportunities for them. Applicants with severe disabilities will be given preferential consideration if they have the same qualifications.
We look forward to your application!
Please send your documents (cover letter, CV, copies of degrees/certificates and references) with reference number 2026_W09_L as a single pdf-file before October 15, 2026 via e-mail tojobs@dife.de.
For further information please contact
Prof. Dr. Stefan Konigorski
Head of the Department of Computational Precision Nutrition
E-Mail: Stefan.Konigorski@dife.de
We process your application documents for the purpose of carrying out the application procedure in accordance with Art. 6 para. 1 lit. b) GDPR, Art. 88 GDPR. For more information on the collection, processing and use of personal data by the German Institute of Human Nutrition as part of the application process and your rights under data protection law, please contact the Department of Human Resources and Social Services (jobs@dife.de).
