362 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" PhD positions in United Kingdom
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engineering, machine learning, molecular design, and sustainability, helping to create smarter ways of identifying promising sorbents for electrochemical CO2 capture. Over the course of the project
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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis for synthesis. A doctoral position is
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the supervisor’s complimentary research expertise in this area (https://millerresearchgroup.co.uk & https://www.lovelockresearchgroup.co.uk),[8,9 ] this PhD will involve the design and chemoenzymatic synthesis of a
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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to commence on 1st October 2026 are now open at the School of Physical Sciences. The projects available are listed here: https://www.open.ac.uk/science/physical-science/phd-students/current-phd-studentships
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bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.04.2029 Reference no.: 5311 Your responsibilities: As a University assistant, you will contribute to the work group Machine Learning
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channel. This will be followed by designing a new resilient waveform for UOWC and developing a computer-based simulation to evaluate its performance. Finally, the study will use existing UOWC channel
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling