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Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, establishing measures of performance, and human data collection in laboratory and field environments.
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NSA Research Scientists are actively expanding the boundaries of what can be accomplished with artificial intelligence, machine learning, human-machine teaming, software reverse engineering, data science, novel architectures, cyber security, high performance computing, and computational linguistics.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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A Ph. D. in accounting, business administration, economics, engineering, finance, industrial/organizational psychology, human resources, political science, public administration, social work, statistics, computer science, management information systems (MIS), quantitative business analysis.
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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PhD in Computer Science, Computer Engineering, Computational Science, Applied Mathematics, Electrical Engineering, Mechanical Engineering or related disciplines.
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Use analytic methods and advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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MS, or above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience What we offer you The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving.
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Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field, with a focus on computer vision, machine learning, or image processing.
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Our current backend stack is Python, Rust, TensorRT-LLM, Kubernetes, AWS. You will work on designing and implementing machine learning models that drive our recommendation systems, retrieval algorithms, and classifiers.
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For this tenure-track position, we seek candidates with expertise in topics including but not limited to (a) healthcare delivery systems; (b) advanced manufacturing, automation, and material handling; (c) applied machine learning and data analytics for manufacturing, logistics, and business decisions; and (d) other advanced topics relevant to industrial engineering.
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As a Machine Learning Engineer at Nelnet, you'll be at the intersection of data science and software engineering. Our Machine Learning Engineer role is at the core of this transformation, creating intelligent systems that automate processes, derive insights, and enable us to make better decisions.
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Degree must be in Network Engineering, Systems Engineering, Information Technology or related field (e.g., General Engineering, Computer Engineering, Electrical Engineering, Computer Science, Computer Forensics, Cyber Security, Software Engineering, Information Assurance, or Computer Security.
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Serves as the experiential learning engine for students majoring in computer science, data science, computer engineering and related disciplines, providing opportunities for students to work on real-world projects learning focused on the application of data science, machine learning, and software engineering skills through a series of practicum courses and labs organized around thematic priority areas such as social justice, sustainability, and civic tech.
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Comprehensive technical expertise and a research track record in one or more of the following domains: artificial intelligence/machine learning; advanced cybersecurity methods and technologies; computer science and engineering; software engineering; modeling and simulation; model-based systems engineering; and/or computational science and engineering.
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machine learning computer science systems engineering equity and inclusion jobs Title: engineering in Anoka, Minnesota
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