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is funded by EPSRC, titled “Adopting Green Solvents through Predicting Reaction Outcomes with AI/Machine Learning”, involving academic investigators from 3 institutions (Imperial College London
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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friendly team you will also receive: Working daily allowance for food and drinks* Free car parking (where available) 25 days holiday plus bank holidays (increasing with length of service) Generous pension
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environments Enjoys helping others learn and grow Is confident using lab or workshop equipment like cement mixers, hydraulic presses, and testing machines Has worked with materials like concrete, soil, or timber
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of Management to develop teaching programmes, and teach and support learning; Use a range of delivery techniques to enthuse and engage students; Will have evidence of excellent teaching identified by peer review
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centres. At Cambridge, our mission is to contribute to society through world-class education, learning, and research. With a deep respect for tradition and a bold vision for the future, we continue to shape
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through various channels, including email, one-on-one meetings, and an online studio space. You will work closely with the course and module leaders to enhance the student learning experience. The role
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the Northeast
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underpinning behaviour (e.g. neurophysiology, metabolism). We are particularly interested in applicants with expertise and research interests in animal-inspired robotics, social and collective behaviour, machine
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(EHR) data built by a multidisciplinary team of software developers, machine learning engineers, clinical researchers and health informaticians. The CogStack team is at the forefront of building