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network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
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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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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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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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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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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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. Mandatory requirements: Demonstrated knowledge of machine learning techniques and programming, with extensive experience in data analysis using Python and R. PhD in Economics, with expertise in health
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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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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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. This large multimodal dataset allows us to estimate and test different computational models of the decision and learning processes. One postdoc is currently working on the MEG and iEEG data, and one PhD