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incremental optimization. We seek researchers to develop next-generation machine learning methods that fundamentally rethink how large-scale AI systems are trained, fine-tuned, and deployed. Our focus is on
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, international group of 13 researchers from 8 countries, with expertise across energy systems and markets, optimization, control, game theory, and machine learning. Interdisciplinary by design: Work at the
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conferences/journals. Aptitude for teamwork, problem-solving, and collaborative relationships Strong technical background in at least one of the following areas: Mathematical optimization, Resource allocation
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-ever Immune Digital Twin – a personalizable computer replica of the immune system – to enable everyone and anyone to assess and optimize the health of their immune system and simulate and predict its
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to introduce world-class industrial data/AI applications into industry. Job requirements BSc (HBO), MSc. (or Ph.D.) in Data Science, Computer Science, Applied Mathematics, Engineering, Physics
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networks also need to evolve, offering, e.g., ubiquitous connectivity and decentralised data-center capabilities to optimize urban performance. This project aims to explore how telecommunications networks
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Group, https://www.chalmers.se/en/departments/e2/research/communications-antennas-and-optical-networks/communication-systems/ , employing around 45 people, including 8 faculty and 25 PhD students. During
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important examples such as Schrödinger Cat states, which are superpositions of coherent states with different phases. This project focuses on the optimal preparation of Schrödinger Cat states in a propagating
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development, analysis procedures, and other engineering solutions. Performs failure analysis, optimization studies and other investigations. Evaluates findings to develop new concepts, equipment, or processes
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options and persuasively advocate for optimal technical solutions, internally and externally. Responsible for responding, triaging, and resolving production system issues in a timely fashion, across