43 structures-"https:" "https:" "https:" "https:" "https:" positions at Technical University of Munich in Germany
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Responsibilities • Develop Probabilistic Machine Learning Models to integrate graphs and food-related omics data • Multi-omics integration using graph-structured prior knowledge • Analyze food-related (multi-)omics
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information of TUM. Kontakt: contmech@mw.tum.de More Information https://www.epc.ed.tum.de/ddmm/aktuelles/article/phd-position-in-collaboration-with-bmw-on-data-driven-modeling-of-structural-foams-for-high
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candidate at TUM and structured doctoral supervision • An excellent interdisciplinary research environment within the Institute for the History and Ethics of Medicine • Close collaboration with national and
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, we are currently looking for a committed PhD Student to start on 15/01/2026. The position is part-time (TV-L 13, 65%) and initially limited to 3 years. Research project Advancements in structural
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(genomics, transcriptomics, proteomics) to uncover structure–function relationships • Integrate experimental data to optimize material properties • Disseminating your project results to the public via peer
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-MS. (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). Ideally, the applicant takes over the co-supervision of selected PhD candidates. We are looking for an individual with a
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of Pittsburgh. This interdisciplinary research aims to advance protein and RNA structural biology and drug interactions by developing and applying innovative ¹⁹F NMR methodologies to study biomolecular structure
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research or practice contexts First experience in prototype construction, mock-ups, or pilot-scale design tests Excellent project management and team coordination skills Proven ability to engage with
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23.10.2025, Academic staff Living systems develop complex structures and functions through principles of self-organization. Stem-cell derived organoids represent a unique platform to dissect
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kinetic mechanisms and key elementary reactions involved. Addressing this shortcoming is the goal of this project. Please visit the DFG research unit description for more information on the topic https