8 bayesian-inference-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" positions at University of Bristol
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projects, including: The post-holder will run numerical models that simulate the dispersion of greenhouse gases through the atmosphere. These models will be used, in Bayesian inference frameworks
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interpretations, in this project, we will use Bayesian statistics and phylogenetic methods to evaluate whether the timing of CSP clade evolution and HGT events are consistent with the oxygenation timeline
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environment, of engineering AI solutions to problems (especially neural networks or large language models) and/or applying data science techniques (such as Bayesian or similar statistical modelling). You should
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, datasets and problems. Experience in handling video data, for learning and inference. Experience in modelling deep learning approaches for Video Understanding. Experience and evidence of publishing at high
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cell types and cell lineages, and to infer the molecular basis of changes in cell proliferation. You have experience in handling large genomic/transcriptomic datasets, genome assembly, annotation and
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health challenges through innovative software solutions. Our research focuses on inferring the causal processes that underlie diseases in diverse populations. Our analytical processes have historically
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inference. We are particularly seeking a candidate with skills in immunology to analyse the blood samples collected across the trial. We are seeking a creative, curious researcher keen to explore
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. metabolomics, proteomics) data in large cohorts Expertise in using standard statistical methods (e.g. regression models) expertise in performing causal inference analyses (e.g. Mendelian randomization, within