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Field
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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of sensorimotor processing. We are recruiting two postdocs: Postdoc in Computer Vision & AI for Behavior Analysis Postdoc in Embodied AI (Reinforcement Learning for Motor Control) Main duties and responsibilities
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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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genomics modalities Background in immunology or inflammatory disease Experience with machine learning methods applied to large data Background in immunology, infectious disease, or inflammatory disease
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; • Familiarity with statistical analyses and modeling as well as machine learning approaches, supported with strong skills in computational optimization of methods; • Experience working with large-scale datasets
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programming languages is required, and experience with the current ATLAS software, computing and particularly the tracking software would be particularly desirable. Experience with machine learning and
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the start date, a PhD in Data Science, Computer Science, Electrical Engineering, Electrical and Computer Engineering, or a closely related field. The applicant’s research should focus on machine learning
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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criteria We seek a researcher with strong machine learning modelling expertise with experience in the analysis of challenging large-scale data sets. Experience with cellular imaging data or virology