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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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project within an NHMRC-funded program focused on dementia research. Using a systems biology framework, the project will integrate genomic and lifestyle data to identify key molecular pathways and risk
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program in partnership with Banner – University Medical Group (B-UMG). Clinical activities will be at Banner MD Anderson Cancer Center, which has an established and growing dermatology program specializing
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unique opportunity to work on advanced image analysis and image-driven modelling as part of a wider multi-disciplinary programme that includes mathematical modelling, cancer metabolomics and novel
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Social Statistics Sociology Academic requirements You must meet the minimum academic requirements for your preferred programme Nationality restrictions This funding is available to all nationalities
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(School of Medicine), Teaching Associate – thomas.bestwick-stevenson@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: The overall
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German Cancer Research Center (DKFZ) Heidelberg • | Heidelberg, Baden W rttemberg | Germany | about 17 hours ago
Heidelberg Teaching language English Languages Working language: English Full-time / part-time full-time Programme duration 6 semesters Beginning Only for doctoral programmes: any time Additional information
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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
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PhD Position in Categorical Foundations of Type Theory Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application deadline: 6
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4‑year PhD position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and