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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to Philip.torr@eng.ox.ac.uk For more information about working
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understanding of dark energy. Projects may span a broad range of topics, including improving Type Ia supernova modelling and standardization, developing and applying advanced data analysis and statistical methods
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on analytical methods, sharing data with partners, and presenting results. The position also demands the capacity to generate new research ideas and support funding proposals, with desirable experience in high
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computational methods, and inn collaboration with permanent academics, help to mentor students undertaking masters projects and internships in the research team. The post-holder will have the opportunity to teach
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project led by Professor Kam Bhui and Dr Roisin Mooney in Oxford. The project investigates methods to improve postpartum outcomes of severe mental illnesses in ethnically diverse mothers (POSIE) with
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quantitative and programming skills along with a track record of designing neuromodulation and neuroimaging studies in healthy participants, of using computer programs to design experimental paradigms, analyse
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using computer programs to design experimental paradigms, analyse data and conduct advanced statistical analysis. You will have excellent communication skills, including the ability to write
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. The group is well known for developing single-molecule and single-cell fluorescence methods (Uphoff PNAS 2013; Zagajewski, Nature Comm Biol 2023, Chatzimichail, Lab-on-a-chip 2024) and applying them
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, Physics, Engineering or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in statistical mechanics method development, with
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an