• Structured PhD training with close supervision in a newly established research group
• Opportunity to work on a highly relevant, interdisciplinary research topic
• lose collaboration with clinical partners and international research networks
• A 6-month research stay at the Institute of Systems Biology, Maastricht University
• Opportunities for methodological development in machine learning and artificial intelligence
• Flexible working hours and a high degree of scientific independence
• Attractive public sector employment conditions (including pension scheme and additional benefits) with one of the largest employers in Lower Saxony
• Comprehensive benefits including structured onboarding, training opportunities, health programs, good transport connections, and bike leasing options

• Analysis and integration of multi-omics data (in particular microbiome, metabolome, and dietary data) from intervention studies and cohort studies
• Development, implementation, and evaluation of statistical models and machine learning approaches to predict individual dietary responses
• Application and further development of methods for integrating heterogeneous data types (e.g., network analysis, probabilistic models, causal inference approaches)
• Development of reproducible analysis pipelines in R and/or Python
• Preparation of scientific publications and presentation of results at international conferences
• Close collaboration with clinical partners, bioinformaticians, and nutrition scientists
• Contribution to the development of research questions and project ideas within the group

• Master’s degree (or equivalent) in bioinformatics, data science, statistics, nutrition science, or a related field
• Strong interest in interdisciplinary research at the intersection of nutrition, microbiome research, and data science
• Solid knowledge of statistical data analysis (e.g., regression models, multivariate methods, machine learning) and strong programming skills in R and/or Python
• Ideally, experience in analyzing high-dimensional data (e.g., omics data)
• High motivation to pursue a PhD and ability to work independently
• Team spirit, openness, scientific curiosity, and strong communication and learning skills
• Excellent English skills (written and spoken)

• Motivation letter
• Curriculum vitae (CV)
• Academic transcripts and certificates (Bachelor’s and Master’s, including transcript of records)
• Master’s thesis (or equivalent scientific work) or, alternatively, a short abstract of the thesis (max. 1 page)

For further information please contact Mueller.Mattea@mh-hannover.de.