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of bottom-up energy management to enable the energy transition for citizens, industrial areas and energy access in developing countries, by e.g., developing novel power electronics, coordination algorithms
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disciplinary boundaries towards bioinformatics and computational biology. You do not need to arrive as an expert in both fields. This is what you will do You will develop quantum-algorithm prototypes within
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researcher to work on systems theory for energy-based learning. What are you going to do? As a postdoctoral researcher, you will develop and analyse new algorithms for energy-based learning of complex systems
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, society, and economy. The Φ-lab will bring together early career and senior researchers from a variety of disciplines across EO and disruptive/transformative innovation to help develop innovative EO
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for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific data infrastructure
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, enabling more efficient downstream metallurgical processing and improved metal circularity. Over recent decades, numerous sensing technologies have been developed for metal scrap characterization. Yet
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germanium, and executed quantum algorithms on a four-qubit quantum processor. As a Postdoc researcher, you will explore opportunities with semiconductor quantum technology and aim to push the boundaries in
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to the mathematical foundations of entropy, randomness and irreversibility, with possible directions including large deviation theory, algorithmic randomness, ergodic theory, quantum entropy, operator algebras and
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project focused on developing an advanced machine learning framework for spatio-temporal datasets. The position is for 2.5 years and is partially funded by the Dutch Research Council (NWO) through
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of the project. The Mathematical physics position will contribute to the mathematical foundations of entropy, randomness and irreversibility, with possible directions including large deviation theory, algorithmic