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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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or other relevant discipline. Extensive experience with in vivo two-photon calcium imaging. Ability to work independently. Proactive and creative independent thinker. Ability to problem-solve and
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machine learning, and for precision-aware scheduling in distributed systems. They will design, develop and refine a software prototype system for distributed serving of machine learning models that leverage
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cohort already registered through our SCAD research portal (scad.lcbru.le.ac.uk ), overseeing consent, data collection, and coordination of clinical imaging, DNA, and biomarker studies. The project offers
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. The Research Fellow will join an international team in the project “Imaging the magma storage region and hydrothermal system of an active arc volcano”, funded by the UK Natural Environment Research Council and
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complex epilepsies using a multimodal approach, including clinical phenotyping, genomics, imaging, and other methodologies, with an emphasis on translational impact. About the role We have an exciting
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pipelines. Your primary focus (80% of your time) will be on leading spatial transcriptomics and imaging genomics projects, integrating bulk and single-cell RNA-seq datasets, and applying advanced statistical
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and in combination with existing antifungal drugs. Areas of interest are: development of in vivo imaging assays for understanding efficacy of novel antifungal drugs, determination of resistance
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vivo imaging assays for understanding efficacy of novel antifungal drugs, determination of resistance liabilities of novel antifungal drugs, via both in vitro and in vivo analyses. The role will also