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. This project will rely on recent advances in neural networks to develop machine learning potentials (MLPs) for MD simulations of realistic nanomaterial/coolant-liquids and use these to gain fundamental insights
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Programme for Scientific Discovery (https://science.ai.cam.ac.uk/ ) is a high-profile University initiative promoting the use of machine learning to tackle major scientific challenges. Accelerate Science
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Postdoctoral Research Associate in Machine Learning ( Job Number: 25000466) Department of Computer Science Grade 7: - £38,249 - £45,413 per annum Fixed Term - Full Time Contract Duration: 24 months
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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University of Cambridge About us Contact us Job Opportunities Jobs Applying for a job My applications Right to work What we can offer Living in Cambridge Temporary work Work experience Volunteering Page not found This page cannot be displayed. If you are returning to a previously accessed job...
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at the intersection of machine learning, bioinformatics, and computational pathology. Project Overview: Integrating histopathological imaging with omics (e.g., transcriptomics, genomics, proteomics) holds tremendous
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Job Description Job Alerts Link Apply now Job Title: Research Associate in Machine Learning and Artificial Intelligence (ML/AI) Posting Start Date: 15/04/2025 Job Description: The Role
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for managing smart cities. The team has gained substantial experience in machine learning for road traffic monitoring. They are now keen to thoroughly explore the additional opportunities presented by
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Compensation $15 Limited Term End Date Position Summary Serves as the first contact for the department. Duties & Responsibilities Greets and directs prospective students and visitors; routes telephone calls; and schedules appointments. Coordinates daily activities of the front desk, which...
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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning