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programming, probability theory, and statistical analysis of large datasets using R or Python. A successful candidate should have a Ph.D. in Operations Research, Electrical Engineering, or Industrial
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of the adaptive immune response to blood coagulation factor proteins deficient in individuals with the inherited bleeding disorder hemophilia, namely factor VIII and factor IX. The goal of the laboratory’s work is
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Disorder, and Dementia with Lewy Bodies. The position involves direct human subject interaction and testing, the collection, organization and analysis of electrophysiological and kinematic data, and
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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meetings Key Responsibilities: Development and implementation of study protocols Participant recruitment and collection of participant and laboratory data Statistical analysis of data Authorship
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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questions as to the short and long-term impacts on vascular disease risk. Published work from our laboratory has shown that both subcutaneous infusion of the major tobacco component, nicotine, and inhaled e
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personalized learning experiences that are both effective and engaging. The first component of this work is to develop AI-augmented tools that enable elementary school-aged children to rapidly create
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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& Brian Hargreaves. Partial list of applicable skills: Expertise in MRI physics Experience with raw MRI data management Experience with MRI reconstruction Clinical studies: data collection / analysis Pulse