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Field
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-house experiment results Use state-of-the-art machine learning models to develop a multi-scale droplets evaporation model Assists in co-supervision of Final Year Projects (FYP) or capstone projects
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, United States of America [map ] Subject Area: Computer Science / Artificial intelligence and machine learning Appl Deadline: 2025/11/20 11:59PM (posted 2025/10/23) Position Description: Apply Position Description
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, Physics, or any related field Strong background in machine learning, PINNs and control theory Excellent verbal and written communication skills Proficiency in programming languages in Python and/or C/C++. A
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field Strong background in control theory, optimisation-based algorithms and/or machine learning Excellent verbal and written communication skills Proficiency in programming languages in Python and/or C/C
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wide range of research, including quantum information and simulation, artificial Intelligence and machine Learning, and physics within and beyond the Standard Model at current and future colliders. The
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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quantum information theorists to integrate secure key rate calculations with simulations. Investigate and apply AI and machine learning techniques to improve and support secure-by-design development
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research experience to include: Experience developing novel deep learning methodologies (e.g. transformer models, Convolutional Neural Networks, Auto-encoder models, or LSTM networks). Demonstrable ability
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and sensor systems for remote maintenance and reliable fusion operations. Artificial Intelligence Developing advanced artificial intelligence / machine learning (AI/ML) solutions for fusion science and
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Partnership between UCL and AstraZeneca and to work as part of a cross-disciplinary team across both sites (London and Cambridge). This post is focused on the use of machine learning models of protein