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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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machine learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key
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We are seeking a full-time Postdoctoral Research Assistant to join the Machine Learning Research Group at the Department of Engineering Science (central Oxford). The post is funded by the Wellcome
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PhD in Chemistry or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in computational chemistry, including machine learning
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and clinical neuroscience. This project involves development of machine learning methods for mapping the relationships between diffusion MRI (dMRI) and phase-sensitive OCT (PS-OCT) in the same tissue
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project and is fixed-term for two years, with the possibility of extension. The objective of this project is to carry out computer vision and machine learning research in order to be able to translate
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification
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team working with epidemiologists, parasitologists, mathematicians, machine learning scientists, laboratory technicians, field assistants, health practitioners/policymakers, and global health ethicists
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requires experience in single-molecule imaging biophysics and expertise in at least two of the following: nanopore technology, optical microscopy, machine learning, mass spectrometry, complex optical set-up
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or statistical machine learning. They will have excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings