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experience Contract Type Permanent Job Type Technical & Scientific Professionals Full Time / Part Time Full Time Job Description Overall Purpose: The Mary Lyon Centre at the Medical Research Council Harwell
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applicants will have:*Expertise conducting spatial and statistical analyses*Experience with scientific computer programming in R and Python*Formal training or experience applying quantitative and spatial
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to multitask and work independently as well as in a team. Experience in large-scale research project management and development, knowledge of statistics and big data analysis would be highly desirable. A highly
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highly motivated and come up with independent lines of research enquiry. Prior experience in one or more of the following areas will be an advantage: a) developing and working with infectious clones
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time on 30 September 2025 will be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and
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be responsible for planning experiments in conjunction with Prof Tucker and Prof Curtis, performing experiments, analysing data and mouse colony management. It is expected that the researcher would
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qualifications at the time of hire. D octor in Philosophy (PhD) in Immunology, Cancer Biology, Molecular Biology, Biochemistry or related field in the bio-medical sciences. Experience in cell culture and basic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, western blotting, and cell culture Experience with murine models of bacterial infection Proficiency in experimental design and documentation, data analysis and visualization, and troubleshooting Experience
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program. Minimum Acceptable Education & Experience: Ph.D. in Physics, Nuclear Physics, Particle Physics, or a closely related field at the time of appointment. Demonstrated experience in experimental
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models