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and power (CHP), and application-specific energy storage systems. We are also exploring how quantum computing can unlock new optimization and control strategies in future power systems. Our projects
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systems can augment professionals’ creativity toward concurrent optimization of human health and energy efficiency. This postdoctoral position will help design and evaluate interactive ideation and
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generation Developing and optimizing generative models for de novo binder design Collaborating closely with wet lab scientists who will express and test the designs that have been created Developing scalable
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to improve and optimize stem cell differentiation and manufacturing. As our new colleague you will be part of a diverse and multi-disciplinary team, which is engaged in machine learning and has a drive to make
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to predict bacterial growth from protein sequence and compound molecular structure. Applying generative and predictive models to propose novel compounds optimized for broad-spectrum activity against diverse
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/MS experiments, with emphasis on negative ion mode Develop and optimize fragmentation strategies for peptide analysis under collisional- and electron-based dissociation regimes Investigate gas-phase
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in electrical engineering, computer engineering, computer science, or similar. Strong background in communication systems, optimization, or machine learning for networked systems. Experience and
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inorganic syntheses Develop and optimize electrochemical experiments and measurements Characterize materials and compounds using standard analytical techniques Analyse data and document results Collaborate
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’ creativity toward concurrent optimization of human health and energy efficiency. This postdoctoral position will help design and evaluate interactive ideation and simulation AI supports tools. You will join an
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for the optimal candidate later dates may be negotiated. You can read more about career paths at DTU here . Further information For further information about the research at SurfCat at the Department of Physics