222 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Technical University of Munich
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university degree in engineering (e.g. Computer Science), completed with above-average results • Good skills (both theory and practice) in one or several of the following topics: Computer Vision, Machine
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16.08.2021, Academic staff For the BMBF funded International Future Lab “AI4EO” (https://ai4eo.de/) we are looking for a motivated Science Manager (m/f/d) ABOUT US The International Future Lab
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. Your Profile: The successful applicant must have the following: • M.Sc. in natural sciences, electrical engineering, physics, optics, medical technology, biomedical computing, or a related discipline
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of miniaturized imaging technologies. Your Profile: The successful applicant must have the following: • Ph.D. in natural sciences, electrical engineering, physics, optics, medical technology, biomedical computing
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group in the field of artificial intelligence in Earth observation (AI4EO). It is in closely collaboration with the Department of EO Data Science, Remote Sensing Technology Institute of the German
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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, adversarial attacks, and
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with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep
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demonstration as proof-of-concept implementation in an experimental 6G testbed. Your qualifications MSc in Computer Science or Electrical Engineering Strong background in networking and systems with solid
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or comparable degree in physics, biology, bioengineering, material engineering or a related discipline. You have experimental experience in cell/tissue culture, microfluidics, or a related discipline. You enjoy
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Master’s degree in physics, chemistry, materials science, chemical engineering, or a related field who are excited about applying machine learning and data science to real-world materials challenges