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Requirements: Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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Bachelor’s degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field with 6+ years of professional experience in data science/machine learning.
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The Department of Mathematical Sciences offers undergraduate degrees in Actuarial Science, Data Science, Mathematical Sciences, and Mathematics & Computer Science, and offers graduate degrees in Pure Mathematics, Mathematics Education, Mathematics for Teaching, Applied Mathematics, and Applied Statistics.
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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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Data science, machine learning, optimization models, Master’s degree 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)Doctorate, Masters: Artificial Intelligence.
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Who you areYou will have a BS, MS, or PhD degree in the physical sciences (e.g. Chemistry, Physics, Chemical Engineering) or quantitative field (e.g. Computer Science, Statistics, Applied Mathematics) or equivalent industry research experience.
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We combine expertise across multiple fields: high-performance scientific computing, physics-based modeling and simulation, data science, machine learning, applied mathematics, optimization, statistics, decision support, data analysis and visualization, computer systems architecture, quantum computing, neuromorphic computing, human-technology connections, and others.
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Bachelor's degree in physics, applied mathematics, scientific computation, computer science, materials science and engineering, or a related field with 5 years of relevant experience (3 years with an M.S. or 0 years with a Ph. D.
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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. Experience with machine learning techniques and tools including deep learning, reinforcement learning, and unsupervised learning.
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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Demonstrated ability in machine learning, data science, economist, or applied research roles. Collaborate with game developers, product managers, and analysts to identify applications of data science, machine learning, economics, and statistics in areas such as game economy health, balancing and intervention, in-game marketplace pricing and mechanism design.
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Bachelor’s Degree required from an accredited, not for profit university or college, with degree preferably in Computer Science, Data Science, Statistics, Machine Learning, or Mathematics.
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A degree in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics, Computational Biology, Computational Chemistry or related quantitative field (Masters or PhD preferred for Senior Manager direct hires.
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Data Analytics, Data Science, Statistics, Health Informatics, Biostatistics, Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics.
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The Mathematics and Computer Science Division at Argonne National Laboratory seeks self-motivated and independent Postdoctoral researcher to develop and apply state-of-the-art probabilistic machine learning techniques for the development of efficient and robust surrogate models for scientific machine learning applications.
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