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in the development of cutting-edge statistical methods and machine learning algorithms inspired by massive healthcare datasets. Key Responsibilities Develop innovative statistical methods and machine
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. Research Statement A description of approaches to working in a diverse community. We ask applicants to share their experiences and/or approaches (past, current, or future) to fostering learning, research
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associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated
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in the biological sciences domain, and end-to-end experience with data science projects that leverage data mining, statistics, predictive modeling, generative AI, and/or machine learning algorithms
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. Must be able to operate and work within a collaborative environment and be willing to learn new experimental/analytic techniques. Must also be willing to participate in teaching of graduate course and
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this academic year. We’re looking for two types of predoctoral fellows: “Machine learning” track: you’re very skilled in machine learning, in particular large language models. Ideally, you would have a Masters in
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experience in NLP, AI and Machine Learning, bioinformatics, translational bioinformatics, clinical informatics, clinical research informatics, consumer health informatics, and/or public health informatics are
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University of Georgia Warnell School of Forestry and Natural Resources | Athens, Georgia | United States | 2 months ago
-level tracer data into hydrologic models. You are enthusiastic about the outdoors, conducting fieldwork to collect and analyze tracer data from various sites. You are excited and willing to learn about
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of this work are to 1) develop a more complete understanding of proteomic changes in postmortem muscle and 2) utilize machine learning techniques to predict fresh meat quality based on proteomic, metabolomic
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Strong interest in pursuing a Ph.D. in a related discipline. Proficiency in programming languages such as Python (Preferred) or R. Experience in data analysis, machine learning, deep learning and