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- Technical University of Munich
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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
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the project include mathematical derivation, analysis, and comparison of models, methods, and simulation approaches; rapid prototyping of new ideas in custom code; implementation of new models, methods, and
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technology for bio- and chemical transformations, separations, purifications and formulation applied to pharmaceuticals manufacture; modelling of processing steps and whole processes to support innovation
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university regulations。Applicants should hold a Ph.D. degree, be under 35 years old, and have a background in immunology, molecular biology, or intestinal model research. Preference will be given to candidates
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`liquid-liquid phase separation' (LLPS). We will use programmable, multi-component model systems of biomolecular phase separation to investigate the transport of biomolecular information, stress, and light
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)confinement in string-net models - Quantum field theory, lattice QCD To apply, please send your application via email with the title “PostDoc application” or “PhD application” to application@zachegroup.com
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, robot-human interaction, trustworthy AI, explainable AI, large language models, quantum computing.
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variables, fixed effects for panel data, matching estimators, or machine learning) or other advanced statistical modelling.- Advanced programming skills in Stata, R, Python or a similar software.- Strong
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Commons licenses, open access publishing models, and publisher licensing practices. • Experience providing instruction sessions, presentations, and one-on-one and group consultations to users and advising