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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 months ago
research on population coding and Alzheimer’s disease Key research methods: fMRI (including 7T), MEG, virtual reality (VR), a wide variety of cognitive tasks, psychophysics, machine learning, deep neural
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experience in cell culture is desirable but not mandatory Proficiency in data analysis and processing using standard computer software Ideally, strong communication skills in both German and English You enjoy
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awaits to become part of our renowned research institution. Be part of change Setup of a simulation environment for tool-delivery tasks (e.g. in Isaac Sim) Implementation of reinforcement learning policies
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the Department of Mechanical Engineering at the School of Engineering and Design (SoED) of the Technical University of Munich (TUM) in Garching, focusing on the design and evaluation of human-machine interactions
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dedicated to the areas of „scenario analysis, future trends and technologies“, „aircraft design for civil and military operations“ and „operational analysis and evaluation“. The combination of these research
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In this thesis you will work in the European Space Agency (ESA)-funded project Fast-EO (Fostering Advances in Foundation Models via Unsupervised and Self-Supervised Learning for Downstream Tasks in
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for Digital Humanities is one of Germany′s leading institutions in the fields of digital and computational humanities. Its key areas of focus are digital linguistics, digital heritage, and AI/machine learning
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required What we offer 👥 Team spirit: Creative, interdisciplinary environment with a motivated team, flat hierarchies, and an informal culture. 🖥 Workplace: Excellent range of machines and equipment, as
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | about 7 hours ago
Institute für Kohlenforschung. Group members will therefore have the chance to learn highly diverse techniques, depending on their research focus and interest. Applications Please send your application
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various materials Your goal is to identify the factors that limit the models’ generalizability To this end, you will investigate transfer learning approaches to reduce the required training effort and adapt