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for sustainable production of food by applying your microengineering and material science skills? Here, we can offer you a unique opportunity to do exactly that in a dynamic research environment. In the SOLARSPOON
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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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Job Description The Quantum Physics & Information Technology (QPIT) group at DTU Physics is seeking exceptional individuals for PhD positions in quantum sensing using color centers in diamond. Our
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DTU Management’s Management Science division. The project is led by Professors Stefan Ropke and Richard Lusby and involves international collaboration with leading researchers in machine learning and
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deformation. Responsibilities Develop scientific machine learning methods in close collaboration with team members specializing in experimental techniques and materials science. Utilize unique experimental data
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degrees in either the natural sciences (chemistry, physics, mathematical/computational biology) or in the formal sciences (statistics, computer science, mathematics), but must have a serious interest in
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, including EMODnet, trawl and dredge surveys, commercial catch and bycatch records, coastal vegetation data, citizen science catch rates, and environmental datasets from Copernicus. This will require working
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this position, you are expected to have: A solid foundation in concrete technology, mechanics of materials, and structural engineering A strong interest in experimental research Prior exposure to or interest in
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topic of this project and who have academic training in one or more of the following areas: A master’s degree in chemistry, chemical engineering, materials science, physics, or a related discipline