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, emissions, and productivity. Decision-Support & MCDA Implement a machine-learning-driven multi-criteria decision analysis to rank and select optimal decarbonization pathways. Collaborate with industry and
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, ELISPOT, flow cytometry, B and T cell receptor sequencing, and transcriptomics. You will develop a reproducible informatics and machine learning pipeline to process large volumes of sensitive trial data in
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time will be allocated to teaching or supervision duties. Requirements The successful applicant should have a doctoral degree in statistics, mathematics, machine learning, or other relevant field, and
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and aggression, using optogenetics, in vivo imaging, electrophysiology, and sophisticated machine learning/artificial intelligence analyses of mouse behavior. All projects have translational components
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standardize large-scale multi-omics datasets and build databases Perform integrative and exploratory analyses of multi-omics datasets and apply machine learning methods to uncover underlying biological
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qualified candidates to apply for a postdoctoral research position. The research will focus on statistical modeling, machine learning and trustworthy AI to develop effective and efficient algorithms
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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make a difference in the world! Position Information We are seeking a postdoctoral position focused on the development and deployment of computer vision and intelligent robotic systems through physics
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI