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on the selected fungal strain growth in response to varying carbon sources. The project will develop a software to automate data processing, machine learning model selection and optimisation and enable end-users
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model and calibrate it using the newly acquired data. Lead the application of machine learning approaches to identify patterns in cassava yield from farm-level data, data captured from field sensors as
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develop a software to automate data processing, machine learning model selection and optimisation and enable end-users to design and optimise microbial protein solutions with minimal user intervention
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equivalent professional experience in a field with significant use of both computer programming and advanced algorithmic, statistical or numerical techniques. Direct experience developing and deploying
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independently without direct supervision Excellent communication (written & verbal) skills Biomedical research experience Desirable criteria UpToDate knowledge of machine learning methods applied to clinical
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Location: South Kensington Campus, London, UK Job Summary Applications are invited for a Research Associate position in the intersection of machine learning and communications. The successful
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and collaboration. Duties and responsibilities This is an exciting opportunity to conduct ambitious research at the interface of information theory, statistical machine learning and robotics
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one of the qualifications described. CCC is committed to continuous improvement and innovation in support of student-centered teaching and learning. We are committed to understanding and dismantling
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and/or mounting. Have an established knowledge and/or show aptitude in learning how to use CAD packages for the development of models for 3D printing, or detailed engineering drawings for workshop
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machine learning to CFD-generated datasets. The ideal applicant is a fresh graduate in engineering or in a closely related discipline, with a track record of achievements at the top of their cohorts