49 machine-learning "https:" "https:" "https:" "https:" uni jobs at University of Sheffield
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the Ice Sheet and Sea Level System Model (ISSM). and/or The development of automated (e.g., machine learning) approaches for mapping glacier-surface morphologies on Mars. You will join a cutting-edge
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. This PhD project will build directly on this work by using ideas from machine learning—originally developed to study the movement of larger organisms—to understand how bacteria process information in
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to achieve a sustainable wind farm lifecycle by developing methods for high-value reuse of composite turbine blades. Machine learning and non-destructive evaluation techniques will be developed to efficiently
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with core data analysis and professional skills that are necessary for bioscience research and related non-academic careers. https://www.yorkshirebiosciencedtp.ac.uk Project Description: Are you
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intelligence (AI) is changing how we understand and improve healthcare. This project will use the latest advances in AI to develop new tools that can learn from many different types of medical information
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experiments and cognitive modelling. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience
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, the project proposes to also use machine learning techniques to learn parts of the prior and penalty structure from data in an interpretable way. Examples include mapping liquidity and volatility features to a
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device health status through condition monitoring. AI techniques such as machine learning will be used to optimise gate driver performance and to map gate drive signal attributes to power device health
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physics-based, and data-driven AI-based approaches employing neural-networks and machine learning, this project will develop and validate a multi-time scale DT concept for advanced condition monitoring and
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(Python, C++). - Knowledge of AI, machine learning, control systems, or reinforcement learning. - Ability to work independently, communicate effectively, and contribute to collaborative research. Desirable