32 assistant-and-professor-and-computer-and-science-and-data Postdoctoral positions at University of Florida
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Description: Conduct independent and collaborative research on microbial metabolism and genetics Utilize molecular biology, biochemistry, and omics approaches to study oral streptococci Analyze data, prepare
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, Program and Staff Awards. Leads and manages annual award and recognition ceremony. Data Management and Compliance Oversees internal systems for tracking fellowships and awards. Ensures compliance with
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and analysis pipeline to compute the 3 and 4 point correlation functions of Roman data. Must have PhD in astronomy or physics. This position will be initially awarded for one year, and, contingent upon
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Classification Title: Post Doctoral Associate Job Description: The Department of Electrical and Computer Engineering is seeking candidate for a position at the level of Post-doctoral Associate
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computer science using data-driven techniques (graph theory, ICA, machine learning), in other imaging modalities (DTI; MEG), and in multimodal integration will be relevant. Experience with AFNI/SUMA, SPM, FSL
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Astronomy, Astrophysics, Physics, or Computer Science by the date of appointment. This position will be initially awarded for one year. UF is the state’s oldest, largest, and most comprehensive land grant
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. Experience with statistical characterization of data, preferably within a Bayesian framework. Preferred Qualifications: Experience developing a (semi-)independent scientific research program on topics in
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Classification Title: Postdoctoral Associate Job Description: Center for African Studies and Master of Sustainable Development Practice Program (MDP) seek an instructor for a 2-2 teaching load
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quantitative health sciences and women’s health. The associate will contribute to an NIH-funded grant with a multidisciplinary team of investigators focused on improving outcomes for all women with uterine
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, Environmental Science, Computer Science, or a closely related field Strong programming skills in Python or R Experience with machine learning and deep learning applied to geospatial data Demonstrated ability