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A successful candidate will have a solid background in pure and applied mathematics and/or statistics and a desire to apply theory from these fields to a broad range of remote sensing and sensor modalities.
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The Mathematics Department at the University of California, Santa Cruz (UCSC) invites applications for one or more visiting assistant professors in all areas of mathematics, including algebra, number theory, topology, analysis, and geometry and dynamics.
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Knowledge of and ability to understand fundamental principles related to physics, mathematics, AC/DC electrical theory, heat transfer, fluid flow, thermal dynamics and chemistry. Experience with natural gas fired combustion turbines, heat recovery steam generators (HRSG), electrical, chillers, compressed air, water softeners, and emissions control systems Knowledge of and experience with at least four (4) of the following skills: pipefitting, welding, machining, rigging, rotating machine repair, fabrication, machine alignment, basic vibration analysis, and basis understanding of electrical test equipment.
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PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
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Apply electronic theory, principles of electrical circuits, electrical testing procedures, engineering, mathematics, and related procedures to test, troubleshoot, repair, and calibrate electronic systems and circuit boards to the component level.
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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields.
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Ph. D. in Biomedical Engineering, Applied mathematics, Systems Biology/Pharmacology or related fields, with 5+ years of mathematical modeling & simulation experience specific for. Understanding of theory, principles and statistical aspects of mathematical modeling and simulation.
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Ph. D. in Applied Mathematics, Physics or Engineering with a focus on computational sciences, Computer Science or related area. Expertise in algorithm development associated with any of the following: artificial intelligence, graph theory, statistical methods, and quantum platforms (both fault tolerant and present-day noisy machines.
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You’ll get the opportunity to use your expertise in one or more of the following areas: machine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, Deep Learning, Natural Language processing or computer vision.
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BACKGROUND & COMPETENCIES: Bachelor’s degree in Finance, Economics, Mathematics, or related field 3+ years’ experience in a Treasury role Experience in Treasury Operations Understanding of banking, financial theory and analysis.
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This position requires a fundamental understanding of some electrical and computer engineering concepts, particularly including electromagnetic wave propagation, signal processing, linear system theory, algorithm implementation and analysis, antenna theory, and linear algebra.
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1) Artificial Intelligence Foundations: includes theory and methods for strengthening AI; Natural Language Processing; Learning Representations and Statistical Learning Theory; Explainable AI; games and economic theories in AI.
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Typically a Master’s Degree in Electrical, Mechanical, or Aerospace Engineering or Applied Mathematics or Applied Physics and 6+ years of experience in Guidance, Navigation, or Controls theory, test and analysis.
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Ideal Postdoc candidate: Ph. D. in fields including computational social science, complex systems, physics, biology, computer science, network science, economics, applied mathematics, or other related fields.
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Should have a record of academic excellence, including demonstrated experience in most of the following areas:Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;Engineering: controls, estimation theory, digital signal processing, and machine learning;Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;Probability: statistics and random processes.
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