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We are looking for an adventurous researcher to explore Monte Carlo methods for radiation transport (as part of the EPSRC grant, MaThRad). The Cambridge Nuclear Energy group is developing a modern
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with Monte Carlo modelling skills and a good understanding of the basic radiation dosimetry principles. Optional experimental work spans molecular biology, in vitro cell studies and preclinical in vivo
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, with a relevant PhD is desirable: Interacting particle systems for Monte Carlo methods and rare event simulation Statistical physics for transport modelling Branching structures and or stochastic
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well as impactful combination therapies. The work spans cellular and preclinical tumour and health organ dosimetry and can be easily carried out by somebody with Monte Carlo modelling skills and a good understanding
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multiple expert elicitation. PINCODE aims to address the challenges in such pooling inference, with implementing either exact or asymptotically exact Monte Carlo algorithms. The project is a collaboration
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improvements of the e+e- to hadron cross section measurements which are underlying the SM prediction require Monte Carlo generators with accurate radiative corrections, beyond what is currently available
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are interested in Hamiltonian Monte Carlo and covariance-informed MCMC samplers. The project is a collaboration with Prof. Ziheng Yang (UCL) and Prof. Philip C. J. Donoghue (Bristol University). About You A PhD in
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subject. Experience in molecular simulations (i.e., molecular dynamics and/or Monte Carlo methods) or liquid state theory (e.g., classical density functional theory) is highly desirable. Potential topics