58 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" uni jobs at Nature Careers in United Kingdom
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testing. Experience of working with genomic data at a population scale, including the tools and technologies to manage sophisticated analyses. Experience of statistical and/or machine learning methods
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, plant transformation, plant breeding, computer vision assisted automated phenotyping, machine learning and AI. The role will require working with other institutional stakeholders to scope, design, equip
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the Centre, enables collaborations in data analysis, computational modelling, machine learning and theory. SWC also benefits from interaction with the wider UCL Neuroscience community, which brings together
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of emerging methods in metabolic analysis, metabolic modelling, machine learning, and data-driven biology, identifying opportunities to apply new tools to accelerate discovery. Work closely with experimental
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(e.g. Nextflow) and cloud compute environments (e.g. OCI, AWS, GCP) Familiarity with Bayesian methods, machine learning, or causal inference in the context of biological data Contributions to open-source
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. Collaborate with interdisciplinary EIT Oxford teams to link fundamental cell-developmental genetics research to machine-learning models designed to augment the search for relevant target genes. Requirements
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workshop for digital and conventional manufacturing (CNC, laser machining, additive manufacturing). At Principal level, you will also contribute to management and long-term technical strategy, infrastructure
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of technology which integrates robotics, computer vision, and data infrastructure to enable scalable, reproducible and data rich transformation platforms, supporting the team with subject matter expertise
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holiday pay Pension Life Assurance Income Protection Private Medical Insurance Hospital Cash Plan Therapy Services Perk Box Electrical Car Scheme Why work for EIT: At the Ellison Institute, we believe a
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programme, with St Andrews, promoting general-ism alongside secondary care exposure, ensuring to place patients at the centre of the students’ learning. Graduation of the first cohort is anticipated in 2028