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for the high throughput control of computations and analysis of results. Structure prediction will be performed using the AIRSS and EDDP (machine learning potential) packages, and prior experience in structure
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biohybrid systems for energy conversion, and the candidate will gain skillsets in biocatalysis and (photo)electrochemistry. The successful applicant will explore a range of engineering approaches including
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on Batteries. The post holder will be located in Central Cambridge Cambridgeshire, UK. Energy
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in Science, Technology, Engineering, Mathematics, and Medicine. The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The
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involve the development of engineering principles for dynamic Power-to-X chemical process, considering reactor, separation and heat integration units. Research will be focused on green ammonia production
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Research Assistant / Research Associate in Frontiers of Atomistic Simulation Techniques (Fixed Term)
interested in the application and methodological development of machine learning techniques to combine electronic structure and modern sampling techniques in liquid-phase heterogeneous catalysis. Experience in
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-depth bioinformatic analysis of large single-cell datasets. You will have access to clinical samples from the MitoCamb neurogenetics clinic, to apply and translate novel technology and insights towards a
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in beneficial associations with microorganisms such as the arbuscular mycorrhizal (AM) fungi. AM fungi mine the soil substrate for minerals and deliver these to the host plant at specialized structures
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We are seeking a post-doctoral Research Associate ("post-doc") to join the Machine Learning Group (MLG) (http://mlg.eng.cam.ac.uk ) in the Department of Engineering, University of Cambridge, UK
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). Please quote reference MA40180 on your application and in any correspondence about this vacancy. The Department holds an Athena SWAN silver award for women in Science, Technology, Engineering, Mathematics