519 data-"https:"-"https:"-"https:"-"https:"-"Universidade-do-Minho" positions in Denmark
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academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme
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of computer-aided tools for chemical and biochemical product and process modeling, process synthesis, design, analysis and operation. The tools are applied in the chemical, petrochemical, pharmaceutical
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Danish or Scandinavian context. Language and further information Applicants must be able to teach and supervise in English at university level. If the successful applicant is not fluent in Danish, s/he
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of limited resourcing is desirable have experience in a leadership position (desirable) For further information about the position, please contact Dean Marianne Holmer at +45 60112605. First interviews are
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. We expect applicants to hold a PhD in a relevant field such as techno-anthropology, science and technology studies, human-computer interaction, human-robot interaction, digital health, anthropology
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underlying greenhouse gas fluxes Support training of young researchers in using biogeochemical observations and data analysis Write and contribute to international peer-reviewed publications Contribute
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grant from the European Research Council. The primary challenge in powering AI chips and future data center systems is enhancing the efficiency of voltage regulator modules (VRMs) to meet their
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of these materials. Implementation of artificial intelligence (AI) and machine learning (ML) to establish the connection between the existing models and material data (both literature and the baseline established in
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chemistry parameters, sediment and soil nutrients (especially carbon and phosphorus), and measurements of greenhouse gas dynamics. Experience in handling and analyzing large and continuous data sets covering
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join us. At DTU Chemical and Biochemical Engineering, you will operate at the forefront of computational modelling, integrating high‑fidelity CFD with advanced compartment models and modern data‑driven