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, Isomap), manifold learning, and machine-learning classifiers to extract neural geometry metrics from both species. Systematically compare behavioural and neural data across mice and humans, identifying
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established and emerging bioinformatics, statistical modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics
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clinical or imaging-based research. Familiarity with vascular imaging software, image post-processing, and AI/machine learning applications in clinical or imaging research is desirable. Demonstrates strong
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. Familiarity with vascular imaging software, image post-processing, and AI/machine learning applications in clinical or imaging research is desirable. Baylor College of Medicine is an Equal Opportunity
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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demonstrated through at least one first-author publication: machine learning/computer science, computational biology/bioinformatics, cheminformatics. Individuals should have or be expected to have a PhD with
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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reinforcement learning approaches for autonomous guidewire shaping and control. • Design experiments, validation strategies, and quantitative performance metrics for robotic navigation and wire-shaping systems
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causal analytical foundations of mass transit system performance. The research is expected to contribute both novel methodological advances in statistical modelling, causal inference, and machine learning
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requirements We will consider applications based on the following skillsets. If you do not fullfil all requirements, please still apply (there is room for learning-on-the-job). A PhD in aerospace/mechanical