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postgraduate degree, ideally a PhD, in statistics, machine learning, or a related field. Experience of developing new statistical methods and a strong working knowledge of a statistical software package, such as
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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, genomic, imaging and digital pathology data for colorectal and other cancers. You'll collaborate with cloud and software engineering teams and the e-health hub team to implement OMOP/OHDSI-compliant
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provide guidance to PhD students where appropriate to the discipline Contribute to developing new computational models, techniques and methods Undertake management/administration arising from research
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assessments (LCA) to quantify the environmental impacts of proposed processes and compare them with conventional alternatives. Develop process models using industry-standard software (e.g., Aspen Plus, HYSYS
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provide guidance to PhD students where appropriate to the discipline Contribute to developing new computational models, techniques and methods Undertake management/administration arising from research
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harmonised protocols for clinical sample processing and multiomics approaches (including transcriptomics, genomics, metagenomics etc.). We have joined our teams to provide bespoke support and analysis
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in using Computational Fluid Dynamics (CFD). Experience simulating complex fluid dynamics processes, preferably multiphase reactive flows, using and especially customising CFD software is an essential
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facilities for magnetoencephalography and hyperpolarised MR. The 7T scanner has recently undergone a major hardware and software upgrade and now forms a testbed for the development of the 11.7T system
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in using Computational Fluid Dynamics (CFD). Experience simulating complex fluid dynamics processes, preferably multiphase reactive flows, using and especially customising CFD software is an essential