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, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
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-science and signal-analysis tasks, including processing experimental signals, integrating datasets, developing machine-learning models, and mapping measured fuel properties to SAF performance. For the post
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projects spanning data visualization, human-computer interaction, and human-centered AI. Coordinate scientific project activities, including planning, reporting, and coordination across collaborating
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representation through machine learning. The position is for a fixed term of 3 years and is part of the project “Reaching AI Projections Trustworthy for Unseen Rainfall Extremes (RAPTURE)”, funded by a European
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on cybersecurity that leads
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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statistical methodology, including genomic prediction, crop simulation and machine learning, to improve prediction of crop yield and related traits. Supervision and Researcher Development: Assist with mentoring
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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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reference monitor on top of seL4 for the secure containment of AI agents. We will develop new mechanisms for dynamically controlling agents’ capabilities and information flows, together with machine-checked
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develop and demonstrate innovative, scalable technologies that enhance military readiness, improve warfighter capabilities, and strengthen defense infrastructure. The programs prioritize common sense, cost