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motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques
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strain-rate/high temperature interface contact layer created during LFW of Titanium alloys and the links to key process variables and machine/tooling behaviour. This study will be undertaken using
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modern machine learning, statistical signal processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs
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strain-rate/high temperature interface contact layer created during LFW of Titanium alloys and the links to key process variables and machine/tooling behaviour. This study will be undertaken using
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Location: West Cambridge Fixed-term: The funds for this post are available for 1 year. The Department of Computer Science and Technology is an academic department that encompasses computer science
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validation evidence, using available machine data, dynamometer testing, and HIL methods. The role will also involve documenting methods and results for project deliverables, reports and publications. The post
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modelling, machine learning, or microfluidics. They will also have excellent communication, organisational and problem-solving skills, and a strong interest in interdisciplinary quantitative biology
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motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques
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. Familiarity with automotive systems, electric vehicles, and embedded BMS constraints. Experience with system identification, uncertainty-aware modelling, large datasets, and machine learning. Evidence of
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, including a mixture of classical and quantum mechanics simulations, cheminformatics and machine learning, as well as collaborative software development, providing expertise for a broad range of future careers