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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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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
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candidate, you have an outstanding Master's degree or comparable degree in biology, physics, applied mathematics or related disciplines. As an experimental candidate you have experience in biological systems
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assessments, techno-economic analysis - Advantageous: experience in up-scaling, bioeconomy, and decentralized business models - Proficiency of the English language, both written and spoken - Interest in and