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single-cell sequencing, spatial transcriptomics, and machine learning algorithms to to understand, at the tissue and organ level, how specific cellular communications—from synaptic connectivity to neural
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computer science knowledge. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel AI/ML algorithms and models. Knowledge about hardware architectures, compilers, neural network
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by publication record). Excellent programming and computer science skills. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel ML and NLP algorithms and models and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g
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of the following: Ecosystem Modeling, Machine Learning, Microbiome, Microbial Ecology, Soil Science, or Computational Biology. The positions are for several different projects, including the following: (P1
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excellent opportunity to work in the development of external relationships and to engage in industry-university partnerships at the cutting edge of engineering, computer and data science, technology, natural
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and uses these applications to inform new foundational ML and NLP innovations. The position provides unique access to world-class computing resources, such as the BNL Institutional Cluster and DOE
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learning field. Excellent programming and computer science skills. Preferred Knowledge, Skills, And Abilities Practical experience developing novel ML, LLM, or CV algorithms and models. Experience with state
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at the Computational Science Initiative (CSI), within the Brookhaven National Laboratory. The selected candidate will collaborate on solving inverse problem, relevant for interference lithography process, by deploying
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are currently recruiting motivated Postdoctoral Fellows with a Ph.D., M.D. (or equivalent) and a background in Computer Science, Electrical Engineering, Biomedical Engineering, or related fields. Candidates who