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undergraduate courses related to programming language, operating systems, computer architecture, data structures, and/or algorithms. Participating in service-related activities, such as serving on departmental
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Abrahao (NYU Shanghai) and João Sedoc (NYU Stern). Research Focus Areas Our research encompasses topics in DL and AI, including but not limited to: Deep Learning Algorithms and Paradigms Generative Models
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Sciences Laboratory (SISL). Responsibilities Conduct analysis, modeling, software and algorithm development in various disciplines such as underwater acoustics, ocean propagation modeling and SONAR
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techniques for warehousing and accessing critical information. Recommend and implement tools and algorithms to generate reports and visualization dashboards using appropriate best practices, statistical
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research in computational biology, single-cell ‘omics-based and multimodal machine learning (ML), and, for the candidate with appropriate skills, quantum computing algorithms and software for applications in
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The research group of Sergei Gukov at Caltech is seeking a Post-Doctoral Researcher to join our new team. The selected candidate will contribute significantly to a focused research program in Artificial
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Bioinformatician at the intermediate or senior level. The Breuss laboratory is focused on employing and developing statistical machine learning, bioinformatic algorithms, and related approaches for the detection
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to obtain access to NOAA Computational Facilities. This position is contingent on extramural funding. WHO WE ARE Texas A&M University-Corpus Christi is a vibrant, Hispanic and Minority Serving Institution
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development pertaining to chemical and biological detection. You will gain experience with algorithms, data analysis, Deep Learning, Python, pytorch and /or tensorflow, NLP, genetic algorithm, computer vision
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using jets and heavy-flavor probes. The candidate will also participate in algorithm and software development for the LHCb trigger system as part of the Real Time Analysis Project. A Ph.D. in experimental