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Centre in the Denmark Hill Campus. The applicant should have a PhD in Biomedical Engineering, Medical Physics, Medical Imaging, or a related area (or pending results). They should have good analytical and
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). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored
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grid analytics, and scientific imaging. The successful candidate will design and implement sparse algorithms for large-scale scientific and numerical computations. This role offers an exceptional
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your application. Reference letters may be requested via an electronic submission process as your candidacy is considered. The position is currently limited to 2 years and may be renewed for one more
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will focus on the prediction of genetic interaction networks and image analysis for automated phenotyping. We welcome interest in developing both ongoing and novel research projects in the lab, and are
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data and clinical information. Applicants must hold (or be close to completing) a PhD in a relevant field and have expertise in modern computer vision and AI research. Experience with biomedical data
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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collaborative mindset and bring the following qualifications: a PhD degree in mathematics, with a focus on algebraic geometry; experience with at least some of the following: Fourier—Mukai transforms, Hochschild
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normal and pathological feeding and reward processes. Applicant must hold a PhD or equivalent degree in neuroscience, biochemistry, molecular biology, psychology, computer science, biomedical engineering
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); units such as onboard computers, mass memories, remote terminals and instrument control units*; digital and analogue signal processing electronics for payload/platform functions; front-end acquisition and