87 complex-analysis-mathematics Postdoctoral positions at Pennsylvania State University
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its treatment options in patients with OSA. Newly NIH funded projects also include mathematical modeling and machine learning of models of tissue hypoxia using sleep studies and molecular markers
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, mucosal and epithelial biology, host–pathogen interactions, aging, and related areas. Take responsibility for advancing assigned projects from experimental planning through data generation, analysis
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analysis, factor analysis, or related methods. Experience working with dietary assessment data and translating complex nutritional exposures into epidemiologic research. Record of peer-reviewed publications
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, mathematics, and the physical sciences. AI for Quantum Systems: Apply machine learning and artificial intelligence techniques to improve the characterization, control, calibration, error mitigation, and overall
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collaboration with faculty and research staff at NCEMS, will conduct original research involving proteomics, mass spectrometry data analysis, protein interactions, protein complexes, post-translational
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SPECIFICS The Department of Mathematics in Penn State's Eberly College of Science invites applications for Postdoctoral Scholars through the Center for Computational Mathematics and Applications (CCMA
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complexes. Experience in the following is preferred: human cell culture, insect cell expression system and/or cryo-EM structural analysis. Applications must be submitted electronically and include a
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optimization algorithms for complex trial design spaces. Required qualifications: A PhD or equivalent doctoral degree in biostatistics, statistics, applied mathematics, operations research, computer science
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pathways that regulate hematopoiesis. Our current research focuses are: 1) Study of epigenetic modulation in hematopoietic stem cell differentiation using genome wide and single cell RNA seq analysis; 2
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ability to engage with both quantitative and qualitative analysis of data (e.g., household surveys, spatial data, interviews, and ecological data), including statistical methods to account for trade-offs