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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
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energy densities exceeding LMFP and competitive with NMC. A postdoctoral research position is available on this 3D-CAT project in the area of computer modelling and materials design of lithium battery
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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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attached to the project. The successful applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis
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abilities, with a demonstrated capacity to interpret complex information and provide clear, pragmatic advice. The role requires sound judgment, tact, and discretion in handling sensitive matters, as well as a
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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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for managing your academic research and administrative activities, adapting existing and developing new concepts in relation to the qualitative empirical data gathered in the project, as well as contributing
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on qualifications and relevant skills acquired and will also be determined by the funding available. About you You will hold a PhD/DPhil or be near completion of a PhD/DPhil in a related subject area and have
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) team. The successful applicant will assist with maintenance and servicing of the Department’s analytical facilities, advise on the use of these techniques and in the interpretation of data, and also
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aims to push the limits of label-free mass measurement of biomolecules in solution by integrating advanced optical techniques with state-of-the-art data analysis. Building on recent developments in mass