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PhD student (f/m/d) who wants to take ownership of the software ecosystem behind our computational imaging research – from experimental reconstruction algorithms used inside our lab to robust tools used
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involving Prof. Dr. Michael Bader (TUM CIT, Hardware-aware algorithms for HPC) , Prof. Dr. Felix Dietrich (TUM CIT, Physics-enhanced Machine Learning) , and Prof. Dr. Hartwig Anzt (TUM CIT, Computational
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tuberculosis (TB) screening research, spanning the evaluation of novel, high-throughput molecular tests, innovative screening algorithms, and digital health tools. A core component of the role involves
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. ▪ Working closely with partners at TUD and theoretical researchers on algorithm development, performance analysis, implementation, and experimental validation. To be qualified for this position, you should
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information is contained in these data and develop the computational and statistical approaches needed to extract it. Working closely with experts in imaging technology, algorithm development, biology, and
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Group (EASE IRTG), Empowering Digital Media (EDM), the Research Training Group HEARAZ , the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms
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validation of linear-scaling electronic-structure and optical-response methods. This includes the advancement and use of efficient algorithms, benchmarking against established approaches, and application
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable
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their thesis work in the field of robotics; Strong programming skills in C++ and/or Python, as well as experience in implementing robot learning algorithms; A strong background in control theory, machine
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biochemists developing the labeling agents, data analysts developing analysis algorithms and physicists developing hardware. The candidate The candidate should have a firm base in in vivo imaging and cell