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, MATLAB, or R) Design of controlled experimental systems to test mechanistic hypotheses Application Instructions Interested candidates should submit the following materials through Interfolio: Cover letter
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-scale molecular datasets Programming skills in Python and/or R Strong publication record in related areas Excellence in experimental design and execution Excellent written and verbal communication skills
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implementation Knowledge of networking protocols and architectures PhD or equivalent R&D experience in computer science, networks or communications, and/or experience with at least one of the following areas
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such as SPSS, R, and/or Microsoft Excel Draft conference and journal submissions based on research findings Prepare financial and progress reports, presentations, as well as other research-related documents
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. Applications close Sunday, 8th June 2025 at 11.00pm AEST (R-52134). Please note that interviews have been tentatively scheduled for the week of 16th June 2025. #LI-DNI
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for Bayesian inference Documented experience with programming in either Python or R. Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system Fluent
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to jobs@lshtm.ac.uk . Please quote reference EPH-DPH-2025-04-R. The supporting statement section should set out how your qualifications, experience and training meet each of the selection criteria. Please
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doctoral qualification (or equivalent experience) in a relevant discipline Strong quantitative analysis skills (R, Stata, or SPSS), with a track record of research outputs Experience in health services
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of the principles of clonal evolution Experience analyzing DNA sequencing data Strong Python and/or R programming skills Proficient with standard statistical analyses Strong publication record Excellent written and
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languages such as R or Python is preferred. Candidates should have strong interpersonal skills, work well in research teams, nurture a professional environment, and have a strong commitment to rigorous