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Job Description You will join a supportive and dynamic research team working at the intersection of machine learning and operations research. Your main task will be to design and implement ML
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virtual/augmented/extended (VR/AR/XR) environments to support learning of scientific concepts and practices at the university-level. This work package investigates how such cutting-edge educational
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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Job Description Are you passionate about renewable energy and eager to apply machine learning to real-world challenges? Join our research team at DTU and work on groundbreaking advancements in
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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University of Southern Denmark was established to create value for and with society. Whether our contributions come in the form of excellent research, innovative solutions, education or learning, we must make
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used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
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decision-making. Collaborate with international partners and contribute to joint research activities. Teach and co-supervise students at different levels in courses and associated projects. Publish and
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tasks will be to: Genetic engineering of bacteria. Phenotypic characterisation of engineered strains. Teach and supervise BSc and MSc student projects. You must have a two-year master's degree (120 ECTS
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Policy Implications and Recommendations Case Studies of Successful Innovation Funding Methods The project will employ a combination of methods, including machine learning (ML) and generative AI (GenAI