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between Network Interface Cards (NICs) and computational nodes. The primary aim is to mitigate host-system overhead by introducing ISA extensions that operate seamlessly at the cache and register level
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institutions. You support us in making this cooperation efficient and productive. As Research Associate you will also support our teaching activities in several Bachelor and Master programs offered by the School
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obtaining research qualifications within the TUM Graduate School. The successful candidate is expected to teach Bachelor and Master courses, initiate and supervise third-party funded projects, and conduct
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of the admission requirements of the corresponding TUM doctoral regulations. Requirements We seek an outstanding candidate who brings the following: Excellent master's degree in computer science or related subjects
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at https://arxiv.org/abs/2311.16733 . Your qualifications Successfully completed university degree (Master's or equivalent) in computer science or similar fields (e.g., information systems engineering
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(many primary data are acquired by single cell sequencing), and will develop and employ novel machine learning-guided approaches. Your profile We are looking for highly motivated applicants with following
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team, please send your application together with a strong CV and supporting documentation (including a list of previously taken courses and grades as well as a summary of your Master thesis (not
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at the Master's and/or Bachelor’s level courses. Supervision of Master and Bachelor students. Your Skills: M.Sc. or PhD. with background in robotics, mechanical engineering, aerospace engineering, electrical
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projects. Ideal profile: Academic and Technical Qualifications: Possess an above average Master's degree in Electrical/Power Engineering or a related discipline, with deep knowledge of energy technologies