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Research Fellow (Fusion Shielding Materials) - School of Metallurgy and Materials - 105638 - Grade 7
variety of research methods, such as scientific experimentation, literature reviews. Analyse and interpret data Contribute to developing new models, techniques and methods Disseminating research results
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model of flare vs remission with a 50% relapse rate. Initial data analysis has taken place using the 10x Chromium single cell sequencing identifying putative cellular subpopulations that determine
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guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental
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novel biomarkers by integrating proteomics, metabolomics, and genomics / transcriptomics data with machine learning techniques. The position is to be filled starting November 1, 2025, either full-time or
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data. Apply knowledge in a way which develops new intellectual understanding. Contribute to developing new models, techniques and methods as required by their research project. Present research outputs
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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guidance to PhD candidates within the discipline when necessary. Contribute to the development of novel models, techniques, and methodologies. Engage in administrative duties within the university
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and values diversity acting as a role model and fostering an inclusive working culture Person Specification Essential: PhD (or near completion) in Computer Science, Data Science, AI, or a related field
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Position Details School of Health Sciences Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,130 to £45,413 with potential
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molecular biology and rodent models · Have experience with epigenetic techniques Your qualifications should include: · PhD in Molecular, Cellular or Developmental Biology. · Strong