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Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies that transform dynamic environmental processes
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of mixed phase numerical or analytical flow modelling for icing. Experience conducting and analysing experimental data is desirable. You should have a record of academic publications in the field and be able
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: analytical and forensic science; asthma and allergy; biophysics and cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering
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. Concurrently, you will develop lower order analytical models and perform high fidelity computational simulations to corroborate experimental findings and propose other configurations to be subsequently
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desirable. Strong analytical capabilities and proficiency in the quantitative analysis of large datasets are also required. Click the 'Apply' button below to register an account with our recruitment system
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-related risks linked to international collaboration. To succeed in this role, you will hold a degree or possess equivalent professional experience. You will bring strong intellectual and analytical
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inorganic materials synthesis, heterogeneous catalysis and advanced analytical techniques including synchrotron radiation experiments. Applicants should also have experience in catalyst production systems
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experiments, developing and running bespoke NMR experiments, collating data/recording the results, undertaking analysis and conducting literature analysis as appropriate. The post holder will help to prepare
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to coordinate research activities and meet deadlines in a fast-paced research environment are essential together with strong analytical skills and the ability to interpret complex data. You will have excellent
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on super-resolution fluorescence and CryoET and will need to analyse data. We encourage applicants with a broad experimental-analytical interest, as the job holder will contribute both to the development