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Field
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sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, generative AI, and digital infrastructures. Your Job
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(Computer Science), in the research group “Computer Graphics and Virtual Reality” of Prof. Gabriel Zachmann, within the EU project SENSORAMA (Horizon Europe), we are seeking to fill the following position
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; Solid knowledge of statistics; Experience using machine learning methods and large language models (LLMs) for research; Experience in building and/or using large cultural datasets. We encourage
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analysis, ideally using Python-based tools and frameworks, with familiarity in areas such as statistical modelling, machine learning, computer vision, or optimisation approaches for experimental systems
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adapters should be created and tested for previously selected detection methods, which can reliably bypass these detection methods. Be part of change Researching and implementing novel machine learning
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present. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python skills, preferably some
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project “Analytics for Learning with Machines” (ALMA) The position is TV-L E13, 75%, limited to 3 years, funded by the Deutsche Forschungsgemeinschaft (DFG). The project is a Franco-German collaboration
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 3 months ago
. Experience in machine learning algorithms and tools. Experience in microscopy and image analysis. Effective collaboration in interdisciplinary teams. Strong analytical reasoning and persistence in experimental
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Faculty of Medicine of the University of Cologne | German Cancer Research Center (DKFZ) | Gronau Westfalen, Nordrhein Westfalen | Germany | 3 months ago
appointment according to the “Jülicher Modell”). The chair will be newly established at the NCT West, Campus Cologne (https://nct.dkfz.de/standorte/nct-west.html ). The NCT is a long-term collaboration between
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-related applications Data protection in machine learning (e.g., federated learning, differential privacy) Monitoring and verification/validation of Al-based systems at runtime Trustworthy Al engineering