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Field
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology
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Physical Requirements Sitting at computer workstation for long periods of time; Standing for long periods of time; Repetitive motion; Job Related Travel (occasional); Hazardous Chemicals or fumes; Burns/Cuts
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our team, as well as a willingness to learn new methods and techniques as the projects evolve. This is a one-year full-time appointment with the potential for extension contingent upon successful
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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well as bulk RNA-Seq, Proteomics, and Metabolomics generated from mouse and patient cohorts with rich clinical data - Advanced modeling of arrhythmias using generalized linear models and machine learning
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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first author publications in reputable peer-reviewed journals Advanced quantitative skills (e.g., advanced stats [MLM], machine learning, data mining). Willingness to develop desired skills (see directly
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in Dr. Shanlin Ke’s lab. The overarching goal of Dr. Ke’s lab is to develop computational approaches and leveraging bioinformatics tools, metagenomic sequencing, multi-omics data, machine learning, and
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in clothing manufacture AI and robotics for personalised healthcare, ageing, wellbeing, and transport systems AI and machine learning to enhance efficiency, quality, and sustainability in fashion
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in