663 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"IFM"-"IFM" positions at Nature Careers
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multi-modal sensing for robotic manipulation Contribute to and/or lead the development of research proposals Take the lead in drafting, reviewing, and submitting project deliverables Support and
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technologies responsibly throughout the development lifecycle. Responsibilities include: Teaching courses across software engineering and related areas using inclusive, activity-led, project-based pedagogy
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cellular mechanisms governing the formation and function of the testis, production and function of sperm, fertilisation, as well as early embryonic development – in both health and disease. To this end, we
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projects on the molecular and cellular mechanisms of infectious and chronic inflammatory diseases with the aim to apply this knowledge to the development of improved diagnostics, vaccines and therapeutics
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web-based applications. Assist in the development, implementation, and maintenance of relevant databases or data warehouse. Develop prototypes for cloud portals and visualization tools; programs
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Chromatography (HPLC-SEC) analysis of purified proteins. Molecular assessment of early-stage development candidates (polyreactivity ELISA, CE-SDS, SEC-MALS, DSF) Maintain accurate and timely ELN data Preferred
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. Support development and implementation of standards, policies, and procedures for Environmental services. Research on new techniques to be used in one's own area; Stay updated with the latest trends in
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-year Wellcome Trust Career Development Award held by Dr Samuel Chawner entitled “Characterising the clinical heterogeneity and aetiology of Avoidant Restrictive Food Intake Disorder (ARFID)”. This is an
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the Clinical track, with 80% effort devoted to clinical service and administrative efforts, and the remaining 20% effort will be focused on translational research and career development opportunities. Ideal
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. Côte d’Azur & INRIA), will be focused on the development and the understanding of deep latent variables models for unsupervised learning with massive heterogenous data. Although deep learning methods and