707 computational-physics "https:" "https:" "https:" "https:" "IFM" Fellowship positions in United Kingdom
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career and managing research as well as a transparent promotion process. Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes). Be part of a diverse
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experience) in applied mathematics, physics or engineering, and strong, up-to-date specialist knowledge in analytical and numerical spray modelling and machine learning. Experience with OpenFOAM or similar CFD
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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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balance in the workplace. The Faculty recognises that applicants may seek flexible working patterns which will be considered as part of the recruitment process. please see our working with us website page
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balance in the workplace. The Faculty recognises that applicants may seek flexible working patterns which will be considered as part of the recruitment process. please see our working with us website page
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positions available Background To create and contribute to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research project
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We are seeking a highly motivated and skilled Research Associate/Fellow to join an innovative translational research programme focused on childhood brain cancer. Based at the University
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methods. It may also include quantitative data analysis. The post-holder will take a role in all stages of this process, from conceptualisation to data collection and analysis, as well as writing up and
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Systems Engineering), along with excellent computing and programming skills in multiple languages and environments. You will also need a problem-solving ability to manage and analyse manufacturing datasets
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models and simulations that deepen the understanding of the underlying physics involved. The ultimate goal is to create predictive, physics-based models that optimise and control pharmaceutical