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or commensurate with experience Type of Position Student Position Time Status Full-Time Required Education PhD or MD Required Related Experience Biomedical Sciences Required License/Registration/Certification NA
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
. Helmut Grubmüller) is inviting applications for a PhD Student or Postdoc (f/m/d) - Theory and Methods for Non-equilibrium Theory and Atomistic Simulations of Complex Biomolecules. Possible projects
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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning
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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated
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. To engage in the wider research activities of the Research Group, School or College. To interact closely with postgraduate research students who are studying for a Masters or a PhD and have an agreed role in
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, willingness to learn, and strong listening skills. Passionate about innovation, with expertise in Linux development (Linux on Rail is a plus) and strong persuasive abilities. A PhD in Operating Systems or a
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) combined with machine learning and chemometrics. Key Responsibilities: The Postdoctoral Researcher is primarily intended to support leaf spectroscopy research but will also be involved in other research
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; you will communicate findings in meetings, publications and international conferences. Essential requirements: academic degree (MSc/PhD) in a relevant field (e.g., computer science, bioinformatics
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motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in constrained environments - Data-driven and learning based control - Meta-learning for emergent behavior in