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. The project will involve theoretical or modelling work relating to high energy astrophysics and black hole accretion-powered outflows, using hydrodynamics codes, theoretical calculations and/or the Monte Carlo
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economics, statistics, or a related quantitative discipline and have strong analytical and coding skills. Experience in evidence synthesis, economic evaluation, or infectious disease research would be
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of accelerator physics modelling codes such as Accelerator Toolbox or ELEGANT would be an advantage. The post-holder will have the opportunity to teach. This may include lecturing, small group teaching, and
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proof-of-principle repetition-rate and staging experimentation. The successful candidate will perform duties that include developing/using particle-in-cell computer codes hosted on local and national high
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throughout your work. Experience with data analysis, coding, or malaria immunology is desirable, but training will be provided where needed. This role suits someone who is motivated, curious, and ready to
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proficient in statistical software (e.g., Stata, Python, R) with strong documentation and reproducible coding practices. An excellent communicator, you will be able to work both independently and as part of a
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to completion of) a PhD/DPhil in geotechnical engineering, along with experience in numerical methods, including the implementation of soil constitutive models in finite element code. You should have excellent
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experimental design • Combining models and combining data / Realistic simulation of clinical trials • Developing LLMs to utilise ODEs and ProbML as tools, Code synthesis for causality
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, econometrics or another relevant field. You will have substantial relevant research experience in complex trait genetics, a proven ability to code and a strong publication record. This is a full time, fixed term
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to taking up the appointment. The research requires experience in electronic structure theory. Experience in R-matrix theory, quantum molecular dynamics, and the calculation of observables, as well as coding