246 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof" positions at University of Cambridge
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We are seeking an experienced Service Owner: Grant Management to strategically develop and implement software products for research grants management at the University of Cambridge. This role is
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, experience and enthusiasm to build on current strengths in maintaining and developing a leading research presence. They are likely to hold a PhD or equivalent postgraduate qualification. Standard professorial
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, or be close to completion of, a PhD in a relevant subject such as applied stem cell biology, development, 3D in vitro model systems, or cellular/molecular biology. You will show enthusiasm for epithelial
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science and the experience of practitioners to the world's most pressing geopolitical challenges, we offer a deeper understanding of where these challenges have come from, how they may develop, and how
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practice developments, trends and initiatives related to STI policies, programmes and strategies in selected countries and communicating these to UK policymakers, agency officials and relevant public sector
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the University's central TLA Systems, primarily our VLE service, Moodle. You will join a supportive and collaborative team, with a management structure that will invest in, and back up your personal development
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diversity. We work to identify the genes that regulate plant development, describe the evolutionary histories of these genes, and connect the molecular evolution of developmental genes to the evolution
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and purification, or with intrinsically disordered proteins, is desirable. Full training will be provided, and the role offers an excellent environment for professional development in
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quality service, efficiency and cost effectiveness in all areas. Utilising well-developed and effective communication skills, the postholder will assist in providing a smooth operation which deals
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kidney cancer research. This is an exciting opportunity to contribute to a large-scale, collaborative project investigating the genomic evolution of kidney cancer, using a uniquely rich cohort of patient