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leverage state-of-the-art deep learning techniques to address challenges in visual data processing and forensic analysis. As part of a dedicated, collaborative research team, you will push the boundaries
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of Machine Learning and Computational Chemistry. This recruitment is linked to the Wallenberg AI, Autonomous Systems and Software Program (WASP) and Wallenberg Initiative Materials Science for Sustainability
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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are looking for candidates with a PhD in Computer Science, Visualization and Media Technology, Machine Learning or a closely related research field. A strong background in machine learning and visual data
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are looking for candidates with a PhD in Computer Science, Visualization and Media Technology, Machine Learning or a closely related research field. A strong background in machine learning and visual data
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, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the world. The employment
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of properties. The project will involve machine learning, and will be performed in close collaboration with the Department of computer science. We have a strong track record in the discovery of both 2D and 3D
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be taken into consideration. We are seeking applicants who have a doctoral degree in a relevant technical area such as AI, machine learning or similar. It is required that you have knowledge and
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a team and be willing to learn from your co-workers and share your knowledge and experience with them in return. You are expected to contribute to the training of junior group members. The workplace
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of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and