239 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"University-of-Southampton" positions at University of Cambridge
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highly-selective and mutant-specific drugs to overcome drug resistance specifically in brain cancer. We are developing new tools to address cutting-edge questions in these fields. This role will be part of
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to the Centre, and will be responsible for its ongoing strategic development, for ensuring that its research programmes remain at the cutting edge of cancer biology and translational cancer research, and for
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allocation within the cell. We are particularly interested in understanding how phenotypic noise can be put under selective pressure. The role will involve developing novel theoretical methods to provide
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creative experiences for audiences, alongside some digital courses (in development) and if required, also supporting outreach opportunities alongside Learning team colleagues. The Fitzwilliam Museum Creative
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pursuit of these goals, we are seeking experienced Machine Learning Engineers (MLE) to lead the development of our software culture. The role holder will contribute to software development activities
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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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assist with the management and development of the full IT infrastructure within CIMR, as well as providing a flexible support service to researchers and administrative staff. This position offers
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civic partners, academic partners, and a project Advisory Board. We are recruiting a Project Curator to support this project. The Project Curator will have a key role in the process of developing
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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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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