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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Ph. D. in Computer Science, Statistics, Artificial Intelligence, Operations Research, Mathematics, Electrical Engineering, Computational Linguistics or related fields. Option 2- Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field.
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Advanced degree in Computer Science, Engineering, Mathematics, Computational Statistics, Operations Research, Quantitative finance or related technical fields. The Data Science Team within Asset Management Technology, Quant Research and Development, is seeking a highly motivated and technically proficient data scientist who is passionate about applying advanced technologies in investment management domain.
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The Mathematics and Statistics Department at San Jose State University offers undergraduate and graduate degrees in pure and applied mathematics and statistics, including the National Science Foundation Noyce-supported undergraduate integrated and Spartan Accelerated Graduate Education programs in single subject credential in mathematics and education specialist credential that serve students with mild to moderate needs.
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Key qualifications: A Ph. D. in Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology and/or computational pathology (required.
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Bachelor's / Master's in Computer Science, Mathematics or Statistics, Computational linguistics, Engineering, or a related field. ML, NLP, LLM Model Evaluation: Work closely with the other data science team members to develop, validate, and maintain robust evaluation solutions and tools to evaluate model performance, accuracy, consistency, reliability, during development, UAT. Implement model optimizations to improve system efficiency.
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Master's or PhD in computer science, applied mathematics, machine learning, data science highly preferred. Bachelor's degree in computer science, applied mathematics, machine learning, data science, or similar technical discipline.
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General understanding of cloud data engineering design patterns and use cases Desired Characteristics: A Bachelor’s degree in Computer Science, Data Science, Statistics, Informatics, Information Systems, Mathematics, Computer Engineering, or a related quantitative discipline is preferred.
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Master’s degree or Ph. D. in a quantitative discipline such as statistics, biostatistics, computer science, bioinformatics, or computational biology. Good understanding of human physiology and molecular biology and how proteomics data can be applied to age-related biological questions.
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Bachelor’s or Master’s degree in Operations Research, Management Science, Data Science, Applied Mathematics, Statistics, Computer Science, or related quantitative fields.
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D. conferred within five years at the time of application or completion of Ph. D. requirements by commencement of appointment in plasma physics, fusion science, engineering (e.g., nuclear, mechanical, electrical, materials, chemical, systems), computer science (e.g., advanced computing and AI for Science), physical chemistry, applied mathematics, or a related field.
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Master’s or PhD in engineering, social science, or related technical field such as statistics, physics, mathematics, operations research, engineering management, computer science, or related STEM program.
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The Department of Computer Science in the College of Engineering at UC Davis, invites applications for a pool of qualified temporary instructors to teach a course in Hacking 4 Climate: business models for addressing climate challenges.
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Candidates with a PhD in bioengineering, computer science, physics, mathematics, statistics, cell and molecular biology, biotechnology, or any related field in the life sciences with strong expertise in computational biology and bioinformatics highly preferred.
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Bachelor's or master's degree in a relevant field such as computer science electrical engineering, computer engineering, software engineering, applied mathematics, or other relevant area, or demonstrably equivalent work experience.
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data science applied mathematics computer jobs Title: risk consultant
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