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-cell data has its own statistical and computational challenges, and standard tools often cannot be applied. The purpose of the position and goal of the project is to develop and apply bioinformatic tools
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novel machine learning-guided approaches. The position is located at TUM Campus Heilbronn. Your qualifications Strong background in computer science, AI, or related areas or similar fields. Solid
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scientific career. About us TUM’s new Computational Pathology and Medical Machine Learning lab (*2021) develops methods of machine learning (ML) and artificial intelligence (AI) for the analysis of digital
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hubs for STS, we are a lively intellectual community of 80+ researchers from numerous disciplines and fields of specialization. As a department, we deliver 2 Master’s programs and design STS content
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, engineering, data science, and computer science. Skill Development: Our extensive qualification concept goes beyond research, offering targeted training in research methods, project management, and leadership
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: - Quantum computing with qudits, quantum error correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de
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Qualifications • You have a degree (Master’s or equivalent) in Civil Engineering or Mechanical Engineering with a strong focus on continuum-solid mechanics and computational methods. • You have experience
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space. We quantify these changes, identify their causes and describe their impacts on biodiversity and ecosystem ser-vices. To do this we use a combination of diverse methods, from empirical research
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and interest in one of the following fields: • Solid state quantum information science. • Quantum optical properties solid-state systems (e.g. semiconductor quantum dots, colour centers in wice gap
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, transcriptomes and epigenomes at an unprecedented level of resolution. To harness the full potential of these developments, new computational methods specifically tailored towards the analysis of single-cell omics