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society. Students learn to analyze complex organizations, identify the causes of suboptimal performance and inequality, and develop and implement effective interventions at the micro (individual) and macro
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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, or similar languages Background in machine learning or deep learning methods Knowledge of genomics, transcriptomics, evolutionary biology, and plant biology is an advantage Familiarity with large biological
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prioritize candidates who specialize in Artificial Intelligence (AI) and Machine Learning (ML), including but not limited to areas such as deep learning, natural language processing, computer vision
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software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing using clusters like UPPMAX and GPUs for high-performance computing and parallel
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, or a related field. Solid research background and practical experience in one or more of the following areas: Reinforcement Learning / Deep Reinforcement Learning Fine-tuning and Application of Large
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initiative on Agentic AI for Scientific Discovery. This project aims to solve a grand challenge in modern AI: developing a deep research assistant capable of accelerating R&D workflows and operations in
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 3 months ago
immunology with deep focus on T cells and Treg biology Hands-on experience with in vivo mouse models (FELASA certification is a strong plus) Practical experience in flow cytometry (FACS), including protocol
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conformational transitions induced by ligand binding, cofactors, metabolites, stress, or post-translational modifications. While recent deep-learning methods such as AlphaFold have transformed protein structure
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!important; } 47 Faculty of Psychology Startdate: 01.11.2026 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Reference no.: 5892 Explore and teach at the University