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The postdoc will join a world-leading research environment at the Chalmers Security & Privacy Lab as a member of the CryptoTeam . The Crypto Team currently has two faculty members and four PhD students
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together all the laboratories, all the PhD students and most of the institution's masters programmes. This institute aims to address the many scientific issues raised by the anthropisation of the coastal
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digital twins require more than visually plausible models: they require analysis‑ready geometry for simulation and decision support. This PhD project develops methods to generate LOD3 urban surface meshes
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commensurate with years since PhD, and a commitment to teaching, mentoring, and external impact that contributes to a strong university community. We seek candidates with research interests in four major areas
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and PhDs in the interdisciplinary project. Your immediate leader is the supervising Professor, and your Line Manager is Head of Department. Duties of the position To develop risk assessment, models
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the interface of biology and medicine, materials science, renewable energy, to chemical engineering processing, material recycling, nuclear chemistry, as well as theory and modelling. The division of Energy and
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qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk
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Anthropology, the MA in Anthropology, the CRM Certificate, and the PhD in Integrated Coastal Studies. Contingent upon availability of funds. Minimum Education/Experience Ph.D. in Anthropology, Archaeology, or a
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contaminant transport from agricultural and natural ecosystems to rivers, lakes, and coastal waters. We are particularly interested in further development and improvement of the bio-physical catchment model
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contaminant transport from agricultural and natural ecosystems to rivers, lakes, and coastal waters. We are particularly interested in further development and improvement of the bio-physical catchment model