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materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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of optimization and machine learning. • Knowledge of reinforcement learning and black box optimization would be a plus. Skills • The candidate must be comfortable with algorithmic development using
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programming, large-scale optimization, and simulation-based optimization; and/or Expertise 2: Experience with general methods in artificial intelligence and machine learning, including reinforcement learning
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assigned. Senior Postdoctoral Associate: Required Qualifications: (as evidenced by an attached resume) Doctoral degree (or foreign equivalent) in Electrical and Computer Engineering or a closely related
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Position Information Posting Number F00749P Position Title Postdoctoral Research Associate - Chemistry and Biochemistry Department Chemistry Location Arlington Job Family Faculty Position Status
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and modelling of omics, clinical and imaging data, development of reproducible pipelines, application of machine learning techniques, integration of multi-modal data, scientific publication and
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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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are expected to have a Ph.D. in theoretical particle physics or related areas prior to the time of employment. Preferences will be given to those with experiences in collider phenomenology, machine learning
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using liquid biopsy next generation sequencing data for cancer diagnostics. About You Must have a strong background in next generation sequencing data analysis/machine learning, cancer and/or genome