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problems. Use the measurement / test data to identify the high-fidelity modelling parameters by solving the inverse problem. Validate the digital model against test scenarios. Perform what-if analyses
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biological models. This position involves the optimization, and operation of an innovative multimodal microscope, as well as close collaboration with experts in the biological sciences for its application
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part of an international team Desired Qualifications Familiarity with cloud computing platforms and large-scale data processing German language skills Publications in computer vision or machine learning
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. Classical cryptographic techniques face inherent limitations, especially regarding future threats from quantum computers or AI-driven adversarial strategies. Physical layer security offers a promising
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research, bioinformatics, and high-performance analytical technologies to explore the complex interactions between the human organism and food components. To strengthen our research group, Integrative Food
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the Leibniz Association. Our institute integrates cutting-edge biomolecular research, bioinformatics, and high-performance analytical technologies to explore the complex interactions between the human
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societal aspects (ELSA) of NeuroAI in the life sciences and biomedicine. The project focuses on (i) neu-romorphic computing inspired by the human brain and (ii) AI-enabled neurotechnologies for clinical and
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advantage. • Passion and drive for an academic career. • High motivation, curiosity, and commitment to scientific excellence. • Team player skills and enthusiasm to work in a interdisciplinary, collaborative
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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry
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team. You will be enrolled in the TUM Graduate School with its structured doctoral program and professional-skills courses. You will contribute to an French-German collaboration on next-generation