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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
, applied mathematics, or a relevant engineering discipline Good programming skills and experience with numerical modeling Interest in performing experiments Excellent written and spoken English skills High
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Job Description The Climate and Energy Policy Division at DTU's Department of Technology, Management and Economics offers a three-year PhD position in the Energy Economics and Modelling section
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supervision from both ends – experimental and computational – and suits students with degrees in molecular biology, biochemistry, mathematics, bioinformatics or any related areas. We open for applications in
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welcomes applications from individuals with a master’s degree in the following fields: Computer Science Mathematics Natural or engineering sciences or an equivalent degree, interested in High-Performance
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Computational Physics, the applicant must have completed at least 90 higher education credits in the subjects of physics, computer science, mathematics, mathematical statistics, or related areas, of which
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Sh.24.3 PhD in Sound Analysis for Predicting Category 1 Ambulance Calls School of Computer Science PhD Research Project Competition Funded UK Students Dr Ning Ma, Prof Jon Barker Application
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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Master’s degree (or other equivalent experience). Suitable backgrounds for these PhD positions include, but are not limited to, power engineering, industrial engineering and operations research, mathematics
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Application deadline: All year round Research theme: Systems and Control How to apply: uom.link/pgr-apply-2425 This 3.5 year PhD project is funded by The School of Engineering and is available