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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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modelling astrophysical phenomena. The PhD project will focus on developing theoretical methods to generate accurate data to meet this demand. The student will gain expertise in high-performance computational
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determined by combining the observed space density of galaxies, the measured spatial distribution of galaxies and simulations of the dark matter distribution. Example themes for student projects follow and
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models. TensorFlow or PyTorch is desirable. How to apply To apply, please ensure you have digital copies of the below information: • Curriculum vitae; encompassing any research presentations and/or
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-style interventions, and preventative medication. Analysis will utilise best practice in health inequalities measurement, modern econometric techniques, behavioural experiments, and modelling
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the diverse range of knowledge and skills of CaLD customers and employees. This project aims to use social identity theory and role theory to develop a comprehensive conceptual model for the process by which
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describing your research interests and why you would like to undertake a PhD (maximum one page) A CV including qualifications, academic achievements, list of publications, work history and references A copy of
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); a copy of academic transcripts for all higher education qualifications; contact details of two academic referees any achievement records Enquiries: Associate Professor Ron Steinfeld Ron.Steinfeld
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applicable); a copy of academic transcripts for all higher education qualifications; contact details of two academic referees any achievement records Enquiries: Associate Professor Amin Sakzad Amin.Sakzad
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experience; a copy of academic transcripts for all higher education qualifications and contact details of two referees (at least one academic referee). a two page proposal Enquiries: should be directed by