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aims to develop responsible transport appraisal methods that consider multiple performance metrics simultaneously, with a special emphasis on fairness to weigh different circumstances, constraints, and
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Your Job: Random unitaries are a ubiquitous tool in quantum information and quantum computing, with applications in the characterization of quantum hardware, quantum algorithms, quantum cryptography
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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. Our supportive workplace fosters a culture of creativity, welcoming fresh perspectives and innovation at all levels. We value teamwork. You’ll collaborate across multiple fields and with the brightest
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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environments, taking into consideration new work arrangements (e.g., gig work and remote work) and technology (e.g., remote control, algorithmic management). The dominance of AT has contributed to an over
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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within a species, going beyond the limitations of single-reference genomes. By integrating multiple genomes from different individuals or populations, pangenomes can provide a more comprehensive
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience