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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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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. Difference between Machine learning, Artificial Intelligence and Deep learning.
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We apply advanced technologies such as Digital Signal Processing, Analytics, Machine Learning, Artificial Intelligence, and Cloud computing to solve our customer and mission challenges.
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Explore new machine learning and artificial intelligence approaches for automated object detection, feature extraction/target state estimation, multi-source data fusion, and much more.
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QinetiQ is looking to hire a Chief Engineer to lead the development of new technologies aimed at advancing the capabilities of airborne C5ISR sensor systems. Nice to have - Altium, SolidWorks, NV-IPM, Zemax, MathCAD.
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The Machine Learning Engineer is responsible for proposing, planning, executing, and analyzing research and development machine learning projects related to the field of advanced manufacturing artificial intelligence.
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PhD in one of the following fields: deep learning, artificial intelligence, machine learning, computer science, robotics, computer vision, computational neuroscience, signal processing, or related fields.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. As a cyber engineer, you will prevent adversary network threats, identify advanced attack vectors, and thwart methods of exploitation.
$65,300 - $149,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Background in Artificial Intelligence (AI), Machine Learning (ML) Natural Language Processing (NLP) Sitting at the intersection of quantitative and investment analysis, the professional will be a "hands-on" player/coach building a team of Data Scientists focused on the implementation of Data Science technologies, techniques and methodologies leveraging Artificial Intelligence (AI) and Machine Learning, advanced analytics, and statistical methods.
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Duties include: Perform Gap analysis and methodologies to identify the implications of artificial intelligence and machine learning for the future of warfare, and the specific defense and security applications (e.g., intelligence analysis, command and control, targeting, autonomous systems, information operations, training and simulation) where AI will be most impactful.
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Implement RMF to support Authorization and Accreditation (A&A) of next-generation autonomous, artificial intelligence, and machine learning systems. ARS is seeking a part-time mid-level Cyber Security Engineer located at Wright-Patterson Air Force Base, OH, supporting the Air Force Research Laboratory (AFRL.
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Develops technical tools and programming that leverage available technologies (e.g., artificial intelligence, machine learning and big-data techniques) to cleanse, organize and transform data and to maintain, defend and update data structures and integrity on an automated basis.
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As part of the Data Engineering team, the Lead Python Data Engineer will work closely with Business domain experts and Data Scientists to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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About the job: We are looking for a Machine Learning (ML) Research Engineer to join our Kilby research and development lab’s embedded Artificial Intelligence (AI) team working on various advanced AI modeling and implementation for time-serious data applications.
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Ever-expanding technology like IoT, machine learning, and artificial intelligence means that there’s more structured and unstructured data available today than ever before.
$58,300 - $133,000 a yearFull-timeExpandApply NowActive JobUpdated Today
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