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. You will develop into an expert in the field while growing as an independent researcher in battery technology. About us The main competencies at the Department of Industrial and Materials Science are
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of Microtechnology and Nanoscience , you will be part of a unique and collaborative research environment in micro- and nanotechnology, housing over 250 researchers and PhD students. The main research activities
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high-quality education at the bachelor's, master's, and doctoral levels, offering over 120 courses each year. We also have extensive national and international collaborations with academia, industry, and
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operation Quantum algorithm implementation and benchmarking About you You have a relevant Masters deegree corresponding to at least 240 higher education credits (Physics, Nanotechnology, Engineering, Computer
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Assisting in departmental teaching, including supervising Bachelor's and Master's theses Contract terms Full-time, temporary position The position is limited to four years, with the possibility of 10-20
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skills in C++, particularly for CFD code development. Basic understanding of structural dynamics in turbomachinery. Experience of working in collaborative or interdisciplinary research environments. Main
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Experience with performing laboratory experiments Ability to work with large data sets (> 500 GB) Numerical modelling Main responsibilities Independent research and research training (80% of time) Support for
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) of geotechnical problems, in particular coupled flow-deformation analyses and/or modelling erosion processes Main responsibilities Conduct independent research and research training (80%) Support education and
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(advantageous but not required). Familiarity with using digital technologies in construction, like BIM (Building Information Modelling). Main responsibilities Participating in the Graduate School of Civil and
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9 PhD students. Main responsibilities • Conduct your own research and take doctoral-level courses to develop your scientific and professional skills. • Present your work and publish your research