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scientific machine learning, knowledge of atmospheric dynamics, new observations, and close connections with national meteorological services, as well as several leading weather forecasting centers and tech
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
large data set types including RNAseq, DNAseq, RIPseq, and CLIPseq. Experience in gene expression analysis, alternative splicing analysis, machine learning, and motif analysis are preferred. Candidates
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. Your profile You have documented expertise in marine ecology and computer vision and machine learning methods for video-based fish monitoring. You have excellent IT skills and experience in handling
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materials science and modular architectures that enable scalable, fault-tolerant quantum computing and quantum-limited sensing. The research program is organized around two large-scale focused efforts
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integrated circuits (PIC). An optical set-up will be used to characterize the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis
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, with a particular focus on Large Language Models (LLMs) and LLM-based systems. Furthermore, there will be the possibiltiy to gain experience as a co-supervisor for the PhD students associated with
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programming, GeoAI, deep learning foundation models, drone and field work experience. Demonstrated high level of achievement in related research productivity and academic writing. Technical skills in computer
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writing course) 324: Social Network Analysis 327: Concepts of Machine Learning 357: Intro to Data Storytelling 426: Museum Informatics 496: Computer Networks 505: Information, Organization, and Access 510
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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling
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statistical and machine learning methodologies to analyze and predict aspects of the collected data With the guidance of Drs. Stuber and Bruchas, develop experimental methodologies related to two-photon imaging