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Field
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contribute to research on applied machine learning methods that support robust decision-making under uncertainty. This may involve working with structured datasets, panel data, text data, regulatory documents
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postdoctoral researcher to join the Immune-Metabolic and Severe Mental Illness Group in the Department of Psychiatry, University of Oxford, to analyse clinical, biomarker and neuroimaging data from major MRC and
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empirical research study to support the investigation of social and ethical dimensions of AI screening tools for mental health risk; from research design, research ethics submission, data collection, analysis
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qualitative and/or quantitative data from a variety of sources, and contribute original ideas for new research projects. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics
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. The Role We are seeking an ambitious research Assistant or Associate who will work with Dr Kavanagh in his EPSRC funded lab (a team of 5 at PhD students and 1 PDRA) to understand the underlying
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computational biologists, immunologists, clinicians, and experimental scientists, you will support study design, data interpretation, and reporting, and contribute to the development of robust, reproducible
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concurrent programming will be particularly desirable. You should have a PhD in experimental High Energy Physics and have the potential to be a leader in the field. Experience with software, computing
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a specific context, conduct individual research, analysing detailed and complex qualitative and/or quantitative data from a variety of sources, and generate original ideas by building on existing
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. PhD awarded in physics, applied
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long