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promoting diverse talent. Reach out to talent@uq.edu.au for accessibility support or adjustments. Applications close Monday, 9 June 2025 at 11.00pm AEST (R-51616). Please note that interviews have been
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Experience with high-throughput sequencing omics data analysis Proficiency in programming with Python, R, or C++ Candidates without a master’s degree have until 31 August 2025 to complete the final exam
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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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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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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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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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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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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
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of epidemiological modelling and data analysis C2 Up-to-date knowledge of epidemiological modelling approaches C3 Knowledge of relevant programming languages for model development, for example Java, R, C++, Julia C4