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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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Neuroscience (IoPPN). The centre aims to better understand the complex interrelationships between society and mental health, with a commitment to: Ensure that the impact of social context is central to how we
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clinicians, who explore the complex social determinants of health, illness and ageing in a global perspective. About the role We are looking to appoint an enthusiastic and highly motivated individual who will
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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
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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the complex interrelationships between society and mental health, with a commitment to: - Ensure that the impact of social context is central to how we understand mental health; - Work in partnership with
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An interest in outreach across policy and civil society and making computation methods accessible. Desirable criteria Experience with independent system dynamic modelling (e.g. not using software such as Vensim
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the complex interrelationships between society and mental health, with a commitment to: Ensure that the impact of social context is central to how we understand mental health; Work in partnership with affected
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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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within medical imaging and computational modelling technologies. Our objective is to facilitate research and teaching guided by clinical questions and is aimed at novelty, understanding of physiology and