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Field
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machine learning-based software applications for materials science Develop code and utilize machine learning to support the automation of characterization and fabrication processes Ensure the integration
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19.04.2024, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Computer Engineering at TUM has open positions for a doctoral researcher (TV-L E13 100%, 3-4 years
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position as PhD student (m/f/d) to develop and implemente machine learning applications and data analysis in Translational Psychiatry. Your group The MPIP Fellowship led by Prof. Dr. med. Falkai at the Max
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in Computer Science or a related field Experience in software development Excellent programming skills Familiar with basics of machine learning Interest in mobility technology and/or simulations, with
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Technology is looking for a research associate (m,f,x) for 3 years, 39,83 hours per week, TVL E13, to work on "Learning-Based Reliable Mixed-Criticality System Design" project. Abstract: A wide range of embedded
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Job description:Title: DC13, PhD fellowship in explainable machine learning techniques to support the design of plant-based fermented food products – Development of a serious game to support the
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
Job description:Postdoc (f/m/d) / Scientific Assistant (f/m/d) Helmholtz AI Machine Learning Scientist With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from
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Deutsches Zentrum für Luft - und Raumfahrt (DLR) | Koln, Nordrhein Westfalen | Germany | about 2 months ago
4 Apr 2024 Job Information Organisation/Company Deutsches Zentrum für Luft - und Raumfahrt (DLR) Research Field Technology Engineering Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country Germany Application Deadline 7 Aug 2024 - 00:00 (UTC) Type of Contract To be...
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"Molecular Modeling" at Leibniz-LSB@TUM is looking for a PhD student (f/m/d) to start on 01/04/2024 Project: The straightforward identification of chemosensory active molecules in food is largely hampered by
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different databases. However, they are not always reusable because they are difficult to find and access and because databases are not systematically interoperable. Please note that this PhD position will