Organisation/Company Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke Research Field Medical sciences § Health sciences Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 31 Jul 2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 3 Jul 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 2026_W07_E Is the Job related to staff position within a Research Infrastructure? No Offer Description 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 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. Roles We are seeking two highly motivated scientists with expertise in Causal Inference / Statistics / Deep Learning / Bioinformatics to join our team. Tasks Develop methods to analyze multimodal digital N-of-1 trials (patient reported outcomes, wearables, images, audio) 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 Contribute to the software development of the StudyU platform for digital N-of-1 trials Perform end-to-end data analysis, including quality control, data integration, and inference of omics data (e.g., transcriptomics, epigenomics, metabolomics) 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 and laboratory scientists in the design of new studies and analysis of existing data Requirements and Skills Excellent master and doctoral degree with demonstrated expertise in at least one of the following areas: Causal Inference, Statistics, Deep Learning, Bioinformatics Expertise with deep learning frameworks Expertise in programming languages such as R or Python Experience with advanced deep learning frameworks
2 Postdocs (m/f/d) / Dept. of Computational Precision Nutrition (CPN) Arbeitgeber: EURAXESS
Die ETH Zürich ist ein hervorragender Arbeitgeber, der eine inspirierende Arbeitsumgebung bietet, in der Forschung und Lehre auf höchstem Niveau stattfinden. Mit einem starken Fokus auf interdisziplinäre Zusammenarbeit und persönlicher Weiterentwicklung unterstützt die Universität ihre Mitarbeiter dabei, ihre akademischen Ziele zu erreichen und innovative Ideen zu verwirklichen. Zudem profitieren die Angestellten von einer vielfältigen und internationalen Gemeinschaft, die den Austausch von Wissen und Erfahrungen fördert.
