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. Expected qualification: High motivation and commitment to scientific excellence Above-average Master Degree / Diploma in engineering (chemical engineering, biochemical engineering, or related engineering
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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fundamental knowledge about the handling and capturing of flow behavior in multistage compressors. The collaborative frame with a prestigious industry partner will give insight to future technology requirements
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13.04.2021, Wissenschaftliches Personal The chair of Software Engineering for Business Information Systems (sebis) at the Technical University of Munich is looking for an excellent candidate for a
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and ability to express yourself in spoken and written German and English language • Proficient use of common programming languages, MS-office, data storage, and image processing • Ability to support the
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that satisfy the user demands in real time while also considering the operator goals of maximizing resource utilization and maintaining service level agreements. The focus of this thesis project will be
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learning to push our understanding of the robustness and explainability of Federated Learning models. Your responsibilities: Build and create clinical use-cases for benchmarking existing state-of-the-art
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clinical use-cases for benchmarking existing state-of-the-art (SOTA) Federated Learning algorithms. This includes running a few pre-processing pipelines. Develop SOTA FL algorithms that tackle data