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A continual learning approach for robust robotic control in electric batteries assembly. This project is an exciting opportunity to undertake industrially linked research in partnership with
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machine learning algorithms and to assess when AI predictions are likely to be correct and when, for example, first principles quantum chemical calculations might be helpful. Predicting chemical reactivity
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Open PhD position: Autonomous Bioactivity Searching Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 42-month funded PhD studentship will contribute to cutting
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-thinking global campuses. An ever changing world where open minds and diverse cultures are able to learn, challenge and create. The success of our university is down to our amazing people and at Nottingham
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confident working with complex data. We are a strong interdisciplinary group and a willingness to learn and work beyond your current comfort zone, supported by an excellent team, would be advantageous
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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cohort to benefit from peer-to-peer learning and transferable skills development. For full information about the programme, the research projects available and how to apply, please visit: http
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to our success, it is fundamental to our values and enriches life on campus. Learn more about the university commitment to Equality, Diversity and Inclusion . We are delighted to share that we
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between chemical and mechanical aspects of sperm cell biology remain largely unknown. In this project a successful candidate will learn, elasticity characterisation techniques, processing and evaluation
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with a background in Chemistry, Biochemistry, Chemical Engineering or a related discipline, who have a strong interest in sustainable chemistry and a desire to learn more about business. The starting