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partners at NHS England and Nuffield Health. About You You will have a PHD (or close to completion) or experience at a comparable level in a relevant subject area. You will have experience of working with
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computational methods (Efremova et al. Nature Protocols, 2020; Jain et al., Genome Biology). About You PhD in a biological or computational subject and background in working with genomics data. About the School
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areas (i) Non-adiabatic chemical dynamics, (ii) Physics of charge transport in the solid state, (iii) QM/MM methods, (iv) Atomistic classical simulations of macromolecules (v) Biophysics. You can write
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data generated by super-resolution STED microscopy, FLIM, FRET and FCS. Candidates must hold a PhD in cell biology, biophysics or biochemistry along with experience in advance quantitative microscopy
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applications to external bodies. Applicants will possess a relevant PhD or an equivalent qualification/experience in a related field of study and be able to demonstrate sufficient knowledge in the discipline and
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modern privacy-enhancing technologies (e.g. based upon synthetic data or using formal differential privacy guarantees) impact research integrity and reproducibility. This is an exciting line of research
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at the Yusuf Hamied Department of Chemistry, University of Cambridge to work on the BBSRC grant "A Platform for Identifying GlycoRNA and Identifying Biases in RNA Pulldown". The role is to develop methods
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quantum field theories, and the application of Hamiltonian methods to gauge theories, though you will also be encouraged to develop and pursue your own research directions. Applicants should have a PhD in
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responsible for the development and implementation of a case study in a US or European city (to be confirmed), using ethnographic and qualitative case study methods under a cross-cultural research design
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in