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Field
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experience developing reproducible and scalable computational workflows for the analysis of complex biomedical data. Experience of using high-performance computing. A proven ability to lead research programmes
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of digital signal processing and data analysis; Knowledge of applied mathematics, statistics, and estimation; Knowledge of scientific programming in Python and/or MATLAB; Programming experience in C/C
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, or related data manipulation and analysis software Strong scientific and technical writing skills Experience with analyzing complex surveys, developing cohort analyses, and testing health outcomes in cross
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the past five years. Preferred skills: Programming and analytical skills in SAS, SUDAAN, Stata, R, Python, or related data manipulation and analysis software Experience analyzing complex surveys, developing
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, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology, operator algebras, complex analysis and
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complex environments. Explore new imaging and sensing approaches that integrate physics-based models with artificial intelligence and conduct research on complex inverse problems and information
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. The position is part of a collaborative project with the University of Edinburgh and the University of Oxford focused on developing scalable methods for complex trait analysis using ancestral recombination
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equations, stochastics and risk, algebra, geometry, topology, operator algebras, complex analysis and logic. We have almost 50 persons in permanent academic positions and a large number of post docs and Ph.D
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collection and analysis for feedback into experimental design. This work will support initiatives within the Agile BioFoundry, the Joint BioEnergy Institute, and/or other programs. This position has
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, stochastics and risk, algebra, geometry, topology, operator algebras, complex analysis and logic. We have almost 50 persons in permanent academic positions and a large number of post docs and Ph.D. students. We