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Bioinformatics Core and Office of AI Research, with opportunities for all fellows to develop their own computational skills). Experimental validation – evaluating RNA drug candidates using cell-based assays
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from you. Dayshift Minimum Education and/or Training: High school diploma/GED Completion of a Nursing Assistant/Medical Assistant program required or completion of foundations of nursing from
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Position Description The successful candidate will be expected to: Develop a research program in omics data analysis in the field of microbial systems biology. The research should adopt a multi-omic
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the course of your doctoral program Our requirements Solid basic knowledge of cell culture as well as isolation of human primary cells Interest and experience in working with bioreactors, especially organ-on-a
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computing and advanced technology, driven by innovation, diversity, and a commitment to excellence. We’re creating an environment where brilliant minds from all backgrounds collaborate to push the boundaries
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PhD students (multiple positions) Artificial Intelligence within Public Health Research (all genders) Start date: 01.10.2026 Contract type: 3 years (fixed-term) Location: Wildau Deadline: 30.04.2026 Remuneration: E 13 TVöD Reference number: 44/26 | 1420262 Be a part of the RKI DNA! The Robert...
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friendly atmosphere of large and interacting communities for e.g. structural biology, molecular cell biology, computational biology, neurobiology, and molecular medicine that encourages lively, open, and
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computational scientists. The position offers a unique opportunity to work at the interface of landscape ecology, biodiversity science, climate mitigation, and sustainable agriculture, contributing directly to
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, equitable, and diverse programme implementation. Conduct strategic analyses and reviews for portfolio development, prioritising investments to achieve impactful, diverse, and equitable research environments
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research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department consists of nine research sections with around 350 highly skilled