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sensor data. Supervisor Bio Dr. Matthew Ellis’ research intersects machine learning and physics; looking to better integrate advances in both to create new paradigms for computing. With a background in
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, Machine Learning, Software Engineering, Chemical Engineering, Civil Engineering, Mechanical Engineering, Robotics, Geotechnology, Operational Research, Computational Physics
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-Joyce ([email protected]) for more information. Learn More: The Leonardo Centre: www.sheffield.ac.uk/leonardocentre John Crane Ltd: https://www.johncrane.com/ More information About the Project
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of Manchester from October 2024. The use of machine learning methods and molecular simulations for polymer design and property prediction is the new frontier in polymer science. This project aims at using a mix
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Machine Learning (ML) models and Python script or equivalent, as well as perform room temperature and cryogenic temperature electrical and mechanical measurements. What You Will Do: Perform mechanical
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Information & e-Horizon Integration: Exploring methods to optimize thermal management system (improving range, efficiency, and passenger comfort). Applying Artificial Intelligence & Machine Learning
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communication and patient intake processes, which may introduce bias in differential diagnoses and disease classification. As part of the project, we aim to develop a machine learning pipeline that will be able
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, machine learning, advanced finite element analysis; Desirable: computer modelling, solid mechanics, experience with Ansys or equivalent software, a final year project on a machine learning/biomechanics
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modelling tools and machine learning methods. The project brings together world-leading experts in both academia and industry, across fields including superalloy metallurgy, microstructure characterisation
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on operations. To support development of complex multi-layered systems and to inform rapid decision-making, this project will develop advanced Machine Learning (ML) architectures that learn directly from a