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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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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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Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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Support energy research by leveraging scientific, spatial, statistical analytics, as well as appropriate artificial intelligence and machine learning algorithms. Experience with and willingness to learn AI (Artificial Intelligence)/ML (Machine Learning) techniques.
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The Leidos Research Support Team (LRST) supporting the National Energy Technology Laboratory (NETL) is seeking a Geology/Geospatial Research Scientist to join our team in Albany, OR or Morgantown, WV. This is an opportunity to execute fundamental and applied research with world-class scientists and engineers using state of the art equipment to perform research aligned with the goals of the U.S. Department of Energy.
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As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Team DescriptionEmerging ML is the data science and machine learning team inside Capital One's Applied Research organization. Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms.
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Data Science, Decision Analytics, Data Mining, Information Sciences, Information Technology, Quantitative Analysis, Operations Research, Operations Analytics, MBAs with Analytical Focus, Engineering, Computer Science, Statistics, Data Management, Decision Science, Quantitative Science, Mathematics, Information Systems, Industrial Engineering, Artificial Intelligence, Computer Vision, Machine Learning, Natural Language Processing.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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We are seeking a Post-Doctoral Research Scientist with a background in Artificial Intelligence, Deep Learning, and Machine Learning to join our Breeding Technologies team in the Seed Product Development group working on Artificial Intelligence in Breeding at our global headquarters in Indianapolis, Indiana location.
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Your Role and Responsibilities As a Senior Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites.
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Ph. D. in Computer Science, Statistics, Artificial Intelligence, Operations Research, Mathematics, Electrical Engineering, Computational Linguistics or related fields. You have/had hands-on experience with Python, Java or Scala and the ability to write reusable and efficient code to automate machine learning pipeline and data processes.
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Ph. D. in Computer Science, Statistics, Artificial Intelligence, Operations Research, Mathematics, Electrical Engineering, Computational Linguistics. and the ability to write reusable and efficient code to automate machine learning pipeline and data processes.
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Emerging ML is the data science and machine learning team inside Capital One’s Applied Research organization. We focus on research and development of new technologies within the domain of Artificial Intelligence with a focus on Embeddings and Foundation Models.
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At least 1 year of experience in open source programming languages for large scale data analysis. Conducting research into self supervised learning, transformer models, and representation learning.
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