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, excipient selection, lead formulation selection, R&D stability batches). Conduct the physical/chemical characterization of all formulations with regard to solution/solid state stability. Evaluates delivery
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. Experience with database development, statistical software (SAS, R), subject recruitment, and laboratory management. Familiarity with EEG and MRI technologies and training in the conduct of human subject
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statistical analysis using R and help organize datasets for interpretation. A key focus will be integrating microbiome and metabolome data through statistical and machine-learning approaches to uncover
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invoices and/or financial reports as required by sponsor. Performs all activities related to closeout. Prepares and sends pre-close memo, final expenditure, and cost sharing letters as needed. Performs A/R
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Development (50%): Develop and apply advanced statistical modeling and coding skills (primarily in R) to build a QMRA framework using data from both the scientific literature and those collected from
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statistical analysis using R and help organize datasets for interpretation. A key focus will be integrating microbiome and metabolome data through statistical and machine-learning approaches to uncover
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and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques. Preferred Qualifications: Prior working experience with EHR data, machine
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model-guided artificial intelligence models for predicting components of agricultural systems, ability to analyze large datasets using Python, R, or other programming languages, and working knowledge
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director of the UF Transportation Institute (UFTI) to drive innovation and expand the impact on congestion, safety, and the economy of university-led R&D on pedestrian, multi-modal, roadway, railway, seaport
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possess: Master's degree in computer science, information technology, or similar discipline and one year of relevant experience. Expertise in Python or R programming. Experience with artificial intelligence