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spatially offset Raman spectroscopy (SORS) as a healthcare tool for use in the community for bone health. We are seeking a data analyst with a PhD in data science and expertise in chemometrics, machine
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the most pressing areas of fundamental understanding which are currently lacking and need to be overcome in order for the four PV device concepts to be optimized. The modelling findings on a range of
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in the annotated and non-annotated genome space. Writing optimised R- or python-based scripts and train group members on using these to analyse their own datasets optimally. Writing scientific papers
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into the same devices. The research project is part of a larger consortium, gathering world-class researchers in remote sensing with expertise ranging from estimation and optimization theory to hardware design
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intelligence (AI) for application in medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics
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medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry
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employed for optimization of the transparency of the Schottky barrier and for promoting performance of Josephson field-effect transistors (JoFETs). With sufficient coherence, these JoFETs components will
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theoretical basis for modelling functional biodiversity, based on eco-evolutionary optimality (EEO) theory. The PDRA will be explicitly responsible for statistical analysis of plant trait data and the
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, fabrication, and testing of functional thin film coatings. Key responsibilities include: Developing and optimizing advanced surfaces using state-of-the-art thin film technologies Characterizing prepared thin
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Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis