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. Advanced programming skills, particularly in Python. Experience with computational approaches to protein folding welcome. Familiarity with molecular dynamics simulation tools such as GROMACS welcome. A solid
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period of up to 12 months in the first instance, with the possibility of an extension, subject to funding. The project entails the development of a kinetic Monte Carlo (KMC) framework for the simulation
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related area, prior to taking up the appointment. The research requires experience in statistical mechanics, and combined simulation/experimental studies of disordered systems. You will be expected
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simulation. You will be expected to manage your own academic research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work to meet deadlines
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Prevention Initiative (COPI). The successful applicant will develop the simulation model capabilities using the PRIMEtime structure to estimate the impacts of the suite of interventions being implemented in
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representations for robust localisation and scene understanding, curate and scale datasets for embodied learning, and transition algorithms from simulation to real-world robot systems. You will collaborate closely
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simulations, generalize experimental observations, and offer insight on the response of selected case studies. You should hold a PhD/DPhil (or be near completion) in numerical modelling for geotechnical
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of agent-based and/or continuum modelling, analysis and simulation. You will have experience of programming in Python and C++, or demonstrated ability to rapidly acquire fluent knowledge of new programming
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Multiphysics software (COMSOL and/or Abaqus), python/matlab coding and Molecular Dynamics Simulator (LAMMPs). 4. Publications in mechanical metamaterials, soft robotics, or related area in peer-reviewed
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach