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aberration in a cellular context. This project will equip the student with a broad range of laboratory and bioinformatic skills relevant to cancer genomics. Number of awards: 1 Start date: September 2026 Award
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/Biostatistics, Data Science, Life and Social Sciences or Medicine (with substantial component and/or experience in quantitative methods), Applied Mathematics, Computing, Quantitative biology, Bioinformatics
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, particularly MRI, medical physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell
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criteria: Knowledge of the molecular basis of ageing, muscle physiology, or the circadian clock. Experience or strong interest in data science, machine learning, or bioinformatics. Exposure to high
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physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell@nottingham.ac.uk . Applications
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. This project will rely heavily on computational analyses, so experience on bioinformatics/informatics is required. The student will receive extensive training in big-data analysis, genome-wide/species-wide
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chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
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library generation, structural biology, organic synthesis, high-throughput screening, mechanistic enzymology, bioinformatics and microfluidic engineering are advantages. Applications should contain a
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Faye Ritchie (faye.ritchie@adas.co.uk ), placement to gain work experience with the agricultural industry Entry requirements Essential BSc in Biological Sciences, Biochemistry, Bioinformatics, Genetics
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at Cranfield University within a supportive, cross-disciplinary environment spanning energy systems engineering, computational modelling, bioinformatics and food safety science. The studentship is funded by