82 modelling-complexity-geocomputation Postdoctoral positions at University of Oxford
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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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data to build hypothesis and test them in laboratory models. You will contribute ideas for new research projects, collaborate in the preparation of scientific reports and journal articles and act as a
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Prof. Luigi Rizzi (Collège de France), seeks to investigate the acquisition of French from a cartographic perspective, employing the Growing Trees model developed by Friedmann, Belletti, and Rizzi, and
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using in vivo models. The role will also include supporting the general program of research within the pre-clinical team. You will work in Containment level 2 and 3 facilities to assist with murine
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array of proteins involved in numerous cellular processes. This complexity can make it challenging to pinpoint disease-relevant changes. By narrowing the focus to the presynaptic proteome, we can reduce
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proteome in heart-specific cell lines and primary tissue. It will utilize disease model systems to characterize unique cell surface signatures for cardiomyocytes, coronary endothelial cells, and fibroblasts
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. The research is primarily translational in nature, involving both preclinical models and human sample analysis from clinical trials, and is carried out in close collaboration with the pharmaceutical industry
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primarily on structural analysis of protein complexes and will best suit a candidate with a PhD and relevant experience in protein biochemistry and structural biology, specifically cryo-EM/ET. The second post
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, the centre will initially focus on some of the following thematic areas: • Decision analysis under model misspecification • Uncertainty quantification around LLMs • Constrained optimal