73 high-performance-computing PhD scholarships at Technical University of Denmark in Denmark
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from related projects at DTU-Bioengineering (https://biocat.ncsu.edu/) and researchers from the private sector. Overall, you will become part of a high-energy, supportive, and inclusive work environment
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-situ spectroscopic and microscopic methods, including XRD, Raman spectroscopy, TEM, and XPS. Evaluating catalytic performance for various electrochemical reactions, such as the oxygen reduction reaction
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fibre-optic sensing technologies and structural health monitoring Skills in data processing and numerical tools such as MATLAB or Python A high level of motivation, intellectual curiosity, and the ability
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Job Description Do you have a background in bioinformatics or AI/ML? Do you wish to do a PhD whereby you use your computational skills to discover new insights in industrially important bacteria
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to efficiently navigate high-dimensional decision spaces, leveraging open-source agent-based simulation tools to evaluate accessibility and environmental impacts of urban planning policies. You should have an MSc
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to foster new ideas and solutions. We collaborate with leading research groups around the world at universities, research facilities, and private companies. At DTU Physics, we perform research and teaching in
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smarter food regulation and enhance microbial food safety within Denmark’s small-scale food processing sector. You will work closely with researchers from DTU Food, DTU Compute, and DTU Management
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of diverse teams with multiple technical and theoretical expertise. Applicable responsibilities for both positions: You are expected to be able to organize and perform your own experiments, and critically
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loads — EV fleets, residential batteries, smart heat pumps, and data-center clusters — across distribution and transmission networks is critical to unlocking deep decarbonization and maintaining grid
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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