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algorithms for real time neural signal processing. Proficient in a range of machine learning techniques, including neural networks, with particular experience in real-time debugging of algorithms during live
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 13 days ago
, 3], significant challenges related to running complex AI algorithms such as Deep Neural Network (DNN) inference on lightweight platforms with limited computational power and relying on potentially
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for projects related to the integration of microgrids, distributed energy resources (DERs), and advanced transmission & distribution (T&D) coordination. This role is ideal for a researcher passionate about
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a Research Engineer to help us develop the next generation of autonomous systems and algorithms for Earth and space applications. Our group doesn't just develop new theories, but puts them to the test
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undersea systems. You will: Design algorithms for vehicle guidance and control in an undersea environment, including signal processing, detection, classification, tracking, and autonomous decision-making
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Majors: -Computer Science -Network Technology -Information and Computer Technology -Software Engineering Analytics and documentation skills are a bonus. Understanding of pseudo-code, designing algorithm
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mindset for all programs, coaches, events and staff. Supervise all online content distributed across departmental mediums including, but not limited to, GoExplorers.com, Twitter, Instagram and Facebook
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acquisition and management. This role directly builds upon Ph.D. research by applying advanced 3D imaging, algorithm design, machine learning, software engineering and visualization techniques to a real-world
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discipline. At least 3 first author papers in disciplines related to neuroprosthetics. Published first author work in using machine learning algorithms for real time neural signal processing. Proficient in a
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation