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
2 Postdocs (m/f/div)
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 two highly motivated scientists with expertise in causal inference / statistics / deep learning / bioinformatics to join our team.
Tasks may include:
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Develop methods to analyze multimodal digital N-of-1 trials (patient reported outcomes, wearables, images, audio) linking causal inference and deep learning
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Develop methodology for individual-level inference of large epidemiological studies (e.g., EPIC-Potsdam study, German National Cohort study) including omics data
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Contribute to the software development of the StudyU platform for digital N-of-1 trials
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Perform end-to-end data analysis, including quality control, data integration, and inference of omics data (e.g., transcriptomics, epigenomics, metabolomics)
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Develop clear data visualizations, reports, and written summaries to communicate results – for scientific publications but also for study participants and patients
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Collaborate with clinicians, epidemiologists, and laboratory scientists in the design of new studies and analysis of existing data
Requirements and skills:
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Excellent master and doctoral degree with demonstrated expertise in at least one of the following areas: causal inference, statistics, deep learning, bioinformatics
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Expertise with deep learning frameworks
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Expertise in programming languages such as R or Python
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Experience with advanced deep learning frameworks and open-source software development
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Strong communication skills and ability to work in interdisciplinary teams
We offer:
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A dynamic, international, and interdisciplinary research environment as well as excellent working conditions and outstanding technical equipment
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Employment with remuneration according to TV-L, level 13, plus annual special payment and company pension scheme
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Family-friendly working conditions (certificate “audit berufundfamilie”)
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Supporting of mobility with a jobticket for using the public transport
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Location close to the vibrant city of Berlin, with easy accessibility by public transport or car
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30 days of vacation
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Participation in the benefits program for employees (“corporate benefits”)
The advertised positions are available for initially three 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_W07_AP as a single PDF file before July 31st, 2026, via e-mail to [email protected].
For further information please do not hesitate to contact:
Prof. Dr. Stefan Konigorski
Head of the Department of Computational Precision Nutrition
E-Mail: [email protected]
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 ([email protected]).
