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sechellensis) as a model system. The project is coordinated by Prof. Jan Komdeur (see: https://research.rug.nl/en/persons/jan-komdeur ), in collaboration with Prof. Martijn Egas (https://research.rug.nl/(...)ons
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Job Description The Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU) invites an excellent candidate to join our team for this full-time position
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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as Electronic Systems, Mathematical Engineering, Software, etc. The integrated stipend consists of two parts, A and B. During part A you are enrolled simultaneous in the Master’s programme and in
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, BCI) Software engineering methodologies, best practices, and tools (e.g., GitHub, Markdown, LaTeX, DVC) Communication Skills: Proficiency in written and oral English (French is considered an advantage
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Supervisors: Prof. Reinhard Maurer (Chemistry), Prof. Richard Beanland (Physics) Understanding how local atomic structure and long-range emergent magnetic and electronic properties in defective 2D
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Supervisory Team: Prof Neil Sandham PhD Supervisor: Neil Sandham Project description: This project is focused on scale-resolving simulations (large-eddy and direct numerical simulation) combined
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machine learning, engineering, data sciences, applied mathematics, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including
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. To meet the general entry requirements for doctoral studies, you must: Hold a Master’s degree in computer science, image analysis and machine learning, engineering, data sciences, applied mathematics
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and a scientific programmer. You will be supervised by both Rianne de Heide and Jelle Goeman. One PhD student will be appointed at the UT, and one PhD student at the LUMC. We collaborate very closely