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be written in German, and the colloquium about the doctoral thesis may be conducted in German. Full-time / part-time full-time part-time (study alongside work) Programme duration 9 semesters or more
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Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent academic record, including
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18.09.2024, Academic staff We have several 𝐏𝐡𝐃 & 𝐏𝐨𝐬𝐭𝐃𝐨𝐜 𝐨𝐩𝐞𝐧𝐢𝐧𝐠𝐬 in our Visual Computing & AI Lab in Munich! Topics have a strong focus on GenAI, including 3DGs, NeRFs, Diffusion
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processing - Study actin-based processes critical for health and disease using the cryo-ET workflow, from cell sample preparation and optimization to imaging and data analysis - Use computational tools for in
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available in the further tabs (e.g. “Application requirements”). Programme Description Are you researching the social effects of digitalisation? Do you want more freedom for your project and are interested in
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the optimal compatibility of studies and practice. We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social
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Informatics. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research environment? Then let’s
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evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine
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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 on semiconductor
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Optimization and Reinforcement Learning methods for problems of design/layout Exploration of Heuristics and Data-driven Methods for the generation of design blocks Automated Test and Verification of designs