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have a PhD, or equivalent advanced or terminal degree from a recognized institution of higher learning, in materials science and engineering, chemical engineering, or related field, with no more than 5
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into the School's activities. We are particularly interested in candidates with expertise in Digital Health and AI in Medicine, including machine learning (especially deep learning), natural language processing, and
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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) approaches. Design predictive maintenance algorithms using machine learning, statistical learning, and digital twin-based models to anticipate failures and optimise maintenance interventions. Integrate AI
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. The work will primarily entail design, implementation, and evaluation of distributed systems and networks for machine learning inference. Applying machine learning concepts, with the goal of devising agentic
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and the selected candidate will be expected to work onsite as of their effective start date. Applicants should be within a few months of completing their doctoral degree or hold a PhD in chemistry or in
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activity should focus on conducting research on machine learning methods, image processing, and advanced data analysis. Furthermore, participation in research projects, active grant applications, and
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models remain a limiting factor in moving to a quantitative scale. Molecular simulation has benefited from recent advances in machine learning and generative artificial intelligence to such an extent
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projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
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/Planning Internal Number: 7006956 Adjunct Faculty - Architecture About the Opportunity The Lecturer will teach introductory courses in architectural drawing, sketching, studio design, computer modeling