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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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women's health. We also have thriving research programmes in global health, and health and social care. Further information about the Faculty of Life Sciences and Medicine may be found at https
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development laboratories at Guy’s Campus, London Bridge. The group specialises in inventing custom fluorescence-lifetime and multiphoton technologies and coupling them with powerful computational pipelines
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of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse single-cell modalities, focusing on gene
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techniques. Motivated and hard-working. Ability to integrate with colleagues, work as part of a team and undertake share of group tasks. Able to carry out learnt techniques unsupervised. Able to plan and
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based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience
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based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience
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context. Able to plan and prioritise workload and keep clear and well-organised laboratory notes and records. Desirable criteria Background in cardiovascular biology Expertise with studying autophagy
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based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD degree in Engineering, Computer