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solid coding skills and hands-on experience with Python for implementing models and analyzing data. Responsibilities include assisting in developing algorithms, running simulations, analyzing results, and
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. Interest in clinical algorithm development and dexterity with biostatistical coding in R or Python is a plus. The primary goal of this aspect of the CH CARE Study is to combine serially obtained somatic and
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. Demonstrated expertise with software development tools and code repositories is required. Expertise in software systems and architecture is required. Experience with scientific programming, algorithms, databases
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. The location, retrieval, and conversion of raw data into usable information is accomplished by implementing a variety of neural network models. Students implement deep learning algorithms for organizing and
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algorithms Improve performance through tuning the GPU code Document, test, and debug revisions of the software for release Coordinate conversion of LM states of cells into coarse-grained atomistic
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Scalable Inference: Develop new algorithms for scalable uncertainty quantification (UQ) and Bayesian inference and apply them to challenging simulation problems. The goal is to produce robust, validated
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. university groups within CMS. Our instrumentation expertise spans detector operations and upgrades (Level‑1 muon trigger, CSC muon system), tracking algorithm R&D, and future HL‑LHC trigger algorithm
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courses on data mining, algorithmic bias, data ethics, and critical data studies. Intermediate and upper level courses could include modeling and simulation, data analytics for spatial analysis, geographic
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Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to contribute to our lab’s mission of aligning machine learning (ML) models with algorithmic reasoning tasks. Our goal is to
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biomedical research projects using programming, data-mining, statistics, machine learning, and visualization techniques to develop, evaluate, and/or apply algorithms and software for data analysis