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) Preparing scientific publications and project reports Your Profile: A successfully completed Master`s degree in the field of engineering or natural sciences or a related course of study Good knowledge
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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, coy of Master and Bachelor degree, letter of motivation, two references for letter of recommendation) in one pdf-document summarized until July 10th, 2024 exclusively via E-Mail: stochastik@uni
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of the doctoral thesis Participation in conferences in Germany and abroad (incl. presenting your research results) Preparing scientific publications and project reports Your Profile: A successfully completed Master
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an eye on the usefulness of the data for the purposes of the users Requirements: Master degree in forestry or agriculture or other landuse related subjects as well as climate or computer sciences Very good
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | about 10 hours ago
technologically. Especially materials that allow for the development of novel memory and computing technologies will be investigated. The main research topics in the research group are currently Iontronics
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the field of fiber design and structure research and write reports and publications in English, or if possible, German language. What you bring to the table Degree (diploma/master) in physics, electrical
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, or if possible, German language. What you bring to the table Degree (diploma/master) in physics, chemistry, electrical engineering or equivalent disciplines Knowledge and relevant professional
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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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excellent degree (Master of Science or equivalent) in Machine Learning or a related field A solid theoretical foundation and practical experience in machine learning Experience in training and evaluation