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Field
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applicant must have the following: • Masters’ degree in Electrical Engineering, Mechanical Engineering, Physics or a related discipline • Experience with electronic circuits design and testing
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report after completion of the research stay? Towards the end of the research stay, the Alexander von Humboldt Foundation asks Siebold award winners to give personal feedback about their experiences in
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university: you will get to know other students quickly, come into contact with other departments and feel at home right away. Our university has an open-door policy: professors are very accessible and happy
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in Life Sciences or in Computational Biology • Experience in flow cytometry, cell culture and in high-dimensional single-cell data analysis and programming skills are a plus • Organizational skills and
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. The main focus is developing and characterizing metallic high-performance materials for/through additive technologies using experiments and computer-aided methods. Furthermore, the chair is dedicated
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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knowledge in Machine/Deep Learning with experience in discriminative models, domain adaptation, and variational inference. Excellent analytical, technical, and problem solving skills Excellent programming
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disciplines). Experience in/Dedication to: planning and conducting chemical experiments, chemical analysis, process modeling/simulation, and optimization Team player skills and enthusiasm to work in a multi
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Engineering or a related discipline. Experiences in Machine Learning, Deep Learning and Artificial Intelligence. Strong programming skills (Python) Good knowledge of AI frameworks like TensorFlow, PyTorch
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://pur.wzw.tum.de/. Application Please send a cover letter that explains how this position fits with your experiences and goals, your curriculum vitae, a list of references and copies of key documents (transcripts