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<span lang="en">International Max Planck Research School for Chemistry and Physics of Quantum Materials</span> | Dresden, Sachsen | Germany | about 19 hours ago
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PhD student in agroecological management for crop resilience to multiple stresses Uppsala Reference number SLU.ua.2026.2.5.1-2269 Department of Crop Production Ecology Research subject: Biology with
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Karlsruhe Institute of Technology | Eggenstein-Leopoldshafen, Baden-Württemberg | Germany | about 19 hours ago
="https://www.iamt.kit.edu">https://www.iamt.kit.edu.
Applications
Multiple positions are available!
Please send applications with CV, publication list and your
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RNAs. The project will integrate RNA sequence, structure, RNA-binding protein interactions, and biological function to uncover the rules governing RNA localization in healthy, degenerating, and
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Spectral Encoding. Develop advanced neural architectures (e.g., adapted Vision Transformers or 1D sequence models) capable of fusing multiple distinct analytical "views" (e.g., combining MS2 and NMR data
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Spectral Encoding. Develop advanced neural architectures (e.g., adapted Vision Transformers or 1D sequence models) capable of fusing multiple distinct analytical "views" (e.g., combining MS2 and NMR data
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decisions. RL & Self-Improving Models: RLHF/RLAIF, online RL, self-play, open-ended discovery, reward modeling, curriculum/active learning, data selection, iterative post-training, safety alignment
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proteome-such as protein-protein interaction patterns, structural similarity, and data-driven embeddings derived from sequence or genetic perturbation-as prior information, complementing or extending
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supervised models on downstream regression tasks. A key challenge lies in effectively modeling the temporal nature of EO data. Since downstream applications require varying temporal resolutions and sequence
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microbial culture capabilities, as well as evaluating culture independent strategies (metagenomics, bioinformatics, synthetic biology) to determine microbial function from sequence data. Since this project