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Field
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. Click to see the full job description Click to find out more about the F Rouhani Lab About you Essential: (Minimum criteria*) PhD (or near submission) in computational biology, machine learning
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data integration and analysis Integrate phylogenomic and functional data using machine-learning approaches for candidate gene prioritisation Contribute to software and web-tool development Present
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, quantitative characterization, and machine learning-enabled decision-making. The position is associated with the recently awarded ERC Consolidator Grant project “Engineering Multivalency for Superselective
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for Optimisation and Machine Learning (QONOMics) project sits at the heart of this expansion. The project focuses on the physics of networks consisting of coupled harmonic and Kerr-nonlinear oscillators. By studying
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps
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processes of the study systems of our collaborators. Core components of the research involve, among others, Bayesian hierarchical modelling, shrinkage methods, machine learning (ML) or dimension reduction
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porphyry copper deposits. In this role, you will develop and apply machine-learning models to predict mineralisation using accessory minerals such as zircon and apatite, with a particular focus on
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on projects at the intersection of computational neuroscience and machine learning. This position is part of a multi-investigator grant on the role of memory in intelligence systems. The Postdoctoral Fellow
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machine learning is an advantage but is not required. Experience with the design and implementation of survey-experiments is an advantage but not a requirement. Alongside developing their own research ideas