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engineering? Then this professor position might be for you. We are looking for a new professor to lead research in probabilistic machine learning, with a focus on areas such as deep generative models, Bayesian
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study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models
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subcellular mechanisms (proliferation, differentiation) with multicellular mechanical and biochemical interactions. Apply Advanced Statistical Methods: Perform Bayesian parameter estimation and identifiability
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generation of health data scientists. Areas of expertise include bioinformatics, computational biology, artificial intelligence, network science, Bayesian methods, spatiotemporal methods, visualization
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Qualifications Current University of Utah graduate student who is supported on the Tuition Benefit Program Preferences Experience using or modifying machine learning models such as decision trees, Bayesian models
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in chemistry and biology, approaches for extracting relevant information from foundation models, and/or methods for adaptive experimental design such as active learning or Bayesian optimization
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Agencies will be returned. Prior to application, further information (including application procedure) should be obtained from the Work at UCD website: https://www.ucd.ie/workatucd/jobs/ Where to apply
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on hormonal time series data collected at unprecedented time resolution in healthy humans and in patients, including studies in real life settings with a state-of-the-art wearable device (https
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development, testing and application of the LPJ-GUESS biosphere model for modelling tropical wetlands and estimating tropical methane emissions. The work is part of the EU-funded project IM4CA (https://im4ca.eu
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. quantitative and/or qualitative counterfactual-based approaches, Difference in Difference models, Qualitative Comparative Analysis, Bayesian hierarchical modelling); o Experience working with and synthesizing