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to work independently and collaboratively within interdisciplinary teams. Background in cybersecurity, machine learning, AI, or large language models (LLM) is advantageous but not a requirement
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technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human
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Compression of quantum data under unreliable entanglement assistance Joint compression and error correction for robust communication in the quantum-classical internet Quantum embeddings for machine learning
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behaviour. This will include developing and using state-of-the-art image recognition algorithms to create digital twin models as well as statistical and machine learning methods for analysing large-scale
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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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knowledge of adaptive control, machine learning and AI. But the most important qualification is an eagerness to learn the mysteries of fuel-combustion-engine interaction. You must have a two-year master's
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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with troubleshooting their machines and support their understanding of core concepts. Guide students in working on their own project. Demonstrate best practices and foster the development