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on innovative design for legal and regulatory systems for AI and other complex global technologies; computational models of human normative systems; and working with machine learning researchers to build ML
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science and artificial intelligence concepts and tools to solve complex problems. Candidates will also be developing machine learning techniques and applying them at scale to specific projects with regular
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foundation models and agentic systems and demonstrated capability to produce workable solutions from theoretical formulations Substantial publication history in top computer vision/machine learning venues
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works to interpret genomes and distill the immensely complex networks that form the foundation of human biology and disease, through accurate machine learning models. Current areas of interest include
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology
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spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques
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for Knowledge-driven Machine Learning. We are looking for a motivated researcher, who has experience with both theoretical, methodological and applied research in change and anomaly detection in sequential data
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quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required
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, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual
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(particularly under extreme conditions), and/or the use of machine learning for solid mechanics/stress analysis problems are encouraged to apply. The job description presented here is deliberately broad due