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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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Familiarity with asynchronous workflows and task queues (e.g., Celery) Knowledge of database design, preferably with relational or graph-relational models (PostgreSQL, EdgeDB/Gel, etc.) Experience working with
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development, integrating quantum communication into classical communication courses, emphasizing both theory and experimental skills, and bridging the knowledge gap between the two fields. Public outreach and
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, optimization, control, game theory, and machine learning. Interdisciplinary by design: Work at the intersection of energy systems and markets, privacy and cybersecurity, forecasting, optimization, control, game
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directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non
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practice as well as in theory. Your primary responsibilities will include: Investigate, develop and validate new models to simulate wind turbine response in HAWC2 at different fidelity levels. Validation
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-assisted control of large wind turbines. You will collaborate closely with both academic and industrial partners in Denmark and abroad, ensuring that your research has impact in practice as well as in theory
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and colleagues working with theory that will complement your work with density functional theory, phase-field simulations, and finite element modelling. Qualified applicants must have: Enthusiasm
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engines. Knowledge of advanced combustion concepts is a merit but not a prerequisite. Practical experience of engine operation in a lab is a merit. Knowledge of control theory is a merit and even better is
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candidate to help develop these new manners by which to promote bonds as kernels in the interpretation of chemical simulations. For this purpose, novel theory and simulation software will need to be developed