21 community-detection-cluster-phd Postdoctoral positions at Chalmers University of Technology
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undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another important aspect involves collaboration within academia and with society at large. The position
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your own research in a research group. The position may also include teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another
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to work on topics at the intersection of applied probability and analysis. The group around Pierre Nyquist currently consists of three PhD students and is focused on questions in probability theory and
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requires sound verbal and written communication skills in English. Swedish is not a requirement but Chalmers offers Swedish courses. You are expected to be somewhat accustomed to teaching, and to demonstrate
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microwave cavities We seek candidates with the following qualifications: PhD in Physics or neighbouring fields Excellent communication skills in written and spoken English Ability to program in high-level
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position is embedded in a vibrant research environment that includes several PhD students and postdoctoral researchers. The project is a close collaboration between the Computer Vision Group at Chalmers
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collaboration with the Multiscale Inorganic Materials group, both part of the Division of Energy and Materials at Chalmers . The two groups together comprise nine senior researchers and 27 PhD students and
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with the project’s Principal Investigator, and practical implementation of this research with the AIMLeNS team. The role also offers ample opportunities to mentor PhD students, supervise MSc projects
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with a focus on nanomaterials and or nanocomposites, awarded no more than three years prior to the application deadline*. You will need strong written and verbal communication skills in English A
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We are seeking a highly motivated and skilled Postdoctoral researcher with interdisciplinary expertise to develop risk assessment and mitigation models using Large Language Models (LLMs