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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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develop, synthesise and characterise materials for this project. About You The post is suited to a PhD graduate with a background in materials chemistry or a related discipline. If you have a vivid
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have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals
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biomedical data scientist / computational biologist to join our highly collaborative team at QMUL. PhD (or close to completion) or research qualification/experience equivalent to PhD level in the relevant
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About the Role To undertake research investigations in collaboration with and under the supervision of Prof Gareth Sanger in order to realise the objectives and development of the research programme
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to work on a project investigating mechanosensing in flies (Diptera). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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with different research expertise and supervising current PhD students in the group. About You Candidates should have a PhD (or close to completion) in mechanical engineering, biomedical engineering or
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work. The candidate is expected to support current PhD students in the group, write and publish research papers. About You Candidates should have a PhD in mechanical engineering, orthopedic engineering