423 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in United States
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development of transparent, closed-loop control system for individualized diuretic closing including the validation and advancement of machine-learning and control algorithms, building production-oriented
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research applying artificial intelligence (AI) and machine learning (ML) techniques to analyze cervid movement patterns. GPS telemetry data obtained from free ranging cervids will be used by the participant
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune
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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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of induced pluripotent stem cell-based human disease models 2) Understanding the role of immunity during tumorigenesis as well as disease relapses in order to design novel inhibitors, CAR-T cell therapy and
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, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited
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, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune microenvironment architecture. Collaborate with wet lab
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of childhood allergic diseases. The candidate will develop machine learning–based biomarker prediction models to identify microbiome-derived signatures associated with allergy risk and immune tolerance outcomes
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of research, testing and data collection, analysis and evaluation, and writing reports which contain descriptive, analytical and evaluative content. The purpose of this role is to acquire the professional
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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic