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both sites. The project sits at the interface of cell line engineering, protein science and machine learning and you will receive advanced training in these areas while developing methods to accelerate
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, at the University of Cambridge, UK. The Postdoc will work together with a team of students and research collaborators on the development of learning-based discovery of robot task/environment designs
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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combines hands-on training, cohort-based learning, and cutting-edge research, preparing graduates for careers in academia, industry, startups, and beyond. We welcome applicants from the Physical Sciences
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development activities such as appropriate professional activities while in the role. This is an excellent opportunity for someone enthusiastic about learning new techniques, proactive in research and self
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) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
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participants Ideally, practical skills in one of (a) programming, (b) machine learning, and/or (c) design Responsibilities Developing and conducting novel research projects individually and on teams Developing a
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level. There is no plan to test any device in the stratosphere. Teaching/learning support, networking and planning the use of resources also takes up a small portion of this position. The skills
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plan to test any device in the stratosphere. Teaching/learning support, networking and planning the use of resources also takes up a small portion of this position. The skills, qualifications and