203 data-"https:" "https:" "https:" "https:" "https:" "https:" "P" research jobs at University of Oxford
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develop new scientific techniques, and test hypotheses and analyse scientific data from a variety of sources. You will contribute ideas for new research projects, develop ideas for generating research
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of the Department. The research activities of the department fall under eight broad headings, though there is much overlap in practice: Information Engineering (Robotics, Computer Vision and Machine Learning
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activities, adapt existing and develop new scientific techniques and experimental protocols, test hypotheses and analyse scientific data from a variety of sources, reviewing and refining working hypotheses as
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streams to meet deadlines. Informal enquiries may be addressed to Professor Oosterbeek and/or Dr Graham (email: reece.oosterbeek@eng.ox.ac.uk or aaron.graham@eng.ox.ac.uk) For more information about working
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meetings, c) analyse archival information and documentation including strategic plans, governance documents, media reports, and policy communications. The postholder will conduct fieldwork across Ghana
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successful careers and build skills in achieving impact, so their findings can influence real-world change. Responsibilities include: • Supporting and conducting data collection across the research
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provide advice and guidance to research students. You will manage your own research and administrative activities, within guidelines provided by senior colleagues. You will gather and manage ecological data
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proof-of-principle repetition-rate and staging experimentation. The successful candidate will perform duties that include developing/using particle-in-cell computer codes hosted on local and national high
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modulation of disease-relevant cellular readouts. The postholder will lead major experimental workstreams within the programme, taking responsibility for experimental design, data generation, and integration
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. They will have experience working with bioacoustic and camera trap data and be familiar with deep learning methods, with a proven track record of training and applying audio signal classifiers. The successful