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Emerging Technologies Group: Covers a wide range of work including Internet of Things (IoT) penetration testing, intelligent automation, artificial intelligence/machine learning and quantum computing.
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There are various disciplines involved in Enterprise Data & Analytics, including: data source identification and analysis, data engineering, data visualization & data science/machine learning.
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Deep understanding of emerging technologies, data analytics, cloud architectures, cybersecurity best practices, and a keen understanding of disruptive technologies including artificial intelligence, machine learning, and quantum computing, and their potential applications within the Intelligence Community.
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Degree: Bachelor’s or Master’s degree in a relevant discipline (e.g., Computer Science, Data Sciences, Decision Science, Engineering, Information Systems, Information Technology, Internet of Things, Applied Math, Machine Learning, Quantum, or other technology majors.
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Basic experience with any of the major Business Intelligence reporting tools, such as Power BI, BusinessObjects, Hyperion, Cognos, Microstrategy, Tableau, QlikView, or SSRS. You will also attend The Intern Challenge, an experiential learning course that will help you transition successfully into your role as an intern.
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During the internship, you will get a preview of Foundations, Protiviti’s innovative entry-level full-time career opportunity, which provides you with experiences and learning opportunities in business operations, consulting, data, relationship building, technology, and innovation.
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The University of Alabama College of Arts and Sciences invites applications for three Assistant or Associate Professor rank tenured/tenure-track positions at the interface of Artificial Intelligence (AI)/Machine Learning and Physics and Astronomy, Chemistry and Geological Sciences, as part of a machine-learning focused cluster hire, with the expected starting date of August 2024.
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The Data Sciences & Machine Intelligence group in the Advanced Computing, Mathematics, and Data Division at PNNL seeks a multifaceted Post Doctorate RA Data Scientist to join the group to lead and support research in scientific machine learning, data-driven control, and robotics.
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We hire curious individuals for whom learning is a passion. The team is skilled in all phases of risk and resilience, from understanding global regulatory requirements and leading practices to designing and implementing right-sized capabilities throughout the business, technology/ cybersecurity, and third-party risk management lifecycles.
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2 years of experience related to new technology (Digital Thread / Twin, Robotic Process Automation, Machine Learning, Artificial Intelligence, Blockchain, etc.) Digitizing the Engineering function with new technologies like Digital Thread / Twin, Robotic Process Automation, Machine Learning, Artificial Intelligence, Blockchain, etc.
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The position requires interest and expertise in statistics, machine learning, artificial intelligence (AI), and medical image analysis. The position requires interest and expertise in statistics, machine learning, and artificial intelligence (AI.
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The Chief Scientist/Technical Fellow should have experience across the important technologies in the sensor technology space, including signal processing, RF and EO/IR hardware, machine learning/artificial intelligence, system integration, field testing, data collection, missions and CONOPs, open architectures and software development, along with a proven track record of delivering quality results to customers in the Department of Defense (DoD) and Intelligence Communities (IC.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. Experience with DevSecOps, CI/CD, IaC and CaC, IT Infrastructure Library, and IT Service Management.
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Stay informed and integrate latest statistical modelling, machine learning, deep learning, recommender system and/or artificial intelligence trends to improve and enhance modelling stack and improve business metrics and customer experience.
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Experience collaborating with business and product leaders to solve open-ended problems using Machine Learning, Artificial Intelligence, and Data Science. Acting as a trusted advisor in matters of Machine Learning, Artificial Intelligence and Data Science.
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