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Proficient in modeling, data collection, data analysis, and statistical analysis tools (ANSYS Maxwell, Comsol, Matlab, Python, JMP). + Experience in architecture, design, characterization, and validation of magnetic sensor or sensing technology that includes theory of operation, signal processing, fabrication, packaging and design trade-offs.
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The ideal candidate will have a strong background in signal processing, statistical modeling, NGS bioinformatics and machine learning with extensive experience in high-plex omics platform development.
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Strong people management skills, experience in data analysis and visualization tools, proficiency in data modeling and manipulation, knowledge of statistical analysis techniques, understanding of data governance principles, business acumen, confident communication and presentation skills, ability to work in a fast-paced environment People Management Snowflake.
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Experience in digital signal processing, statistical modeling, and stochastic processes. The Information Sciences and Modeling group (1) is looking for an outstanding scientist in the field of risk modeling, optimization, and machine learning, with additional expertise in data signal processing and telecommunications network and protocols.
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As a Sr Research Data Scientist, you will be responsible for performing tasks such as data analytics, data clean-up, data processing, ML modeling, statistical analysis, multivariate data analysis as it relates to scientific data.
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Knowledge of radio frequency (RF) transmission theory, to include radar principles, signal reception, signal processing, detection and tracking performance, and electronic protection (EP); electronic warfare system components and dependencies (i.e. antennas, transmitters, receivers, signal processors, cooling systems, onboard power and avionics integration considerations, interrogation friend-or-foe (IFF) systems, etc.
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RF, analog, digital, and / or mixed signal circuit design or analysis and / or digital signal processing. The Receiver, Exciter, and Back-End Processing (REBEP) Department is the focal point for receiver, exciter, beam steering, and signal processing technology within Raytheon.
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Ideal candidates will also have experience in statistical signal processing and its application to sensor data or experience leveraging the latest techniques in deep learning for computer vision.
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ResponsibilitiesConduct analysis, modeling, and algorithm development in various disciplines such as signal processing, statistical modeling, information fusion, underwater acoustics, propagation modeling, and target modeling and tracking.
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Knowledge of adaptive filtering / statistical signal processing Experience with acoustic testing, data acquisitions, and data analysis. Requirement Summary Our Acoustics & Simulation Group is seeking a signal processing engineer to be part of a multi-disciplinary team working on projects that span a wide range of research areas.
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Ready for a challenge that will keep you on the cutting edge of systems engineering, modeling, simulation, and RF signal and data processing techniques? You will have an opportunity to influence the development of next generation advanced radar simulation capabilities that will include being part of a high-performing team that will research, design, develop, and integrate models for various types of radar systems, collaborating across programs to achieve end-to-end solutions, providing analytic, statistical, radio-frequency signal and visual analysis capabilities.
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Engineers in this group have knowledge in the areas of finite element and boundary element analysis, structures, electronic instrumentation and measurements, electronic component design, acoustic theory, signal processing, and system engineering, among others.
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Additional background in optics, spectroscopy, image processing, signal analysis, control, EM modeling, statistical analysis. Strong analytical problem solving skills including knowledge of statistics, statistical analysis Responsibilities.
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Have a PhD degree in Electrical Engineering, Mathematics, Physics, or a related field Have background in one or more of the following broad research areas and related subspecialties: signal processing (adaptive signal processing, statistical signal processing, image processing, radar signal processing, etc.
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In particular, the following expertises are of interest: structured inference (sparse approximation, low rank matrix completion, tensor signal processing, graph signal processing); multi-terminal information theory, or information theory at the boundaries of control or signal processing; distributed control, consensus methods and partially observable Markov Decision Process modeling and algorithms ; modern optimization methods; or biological communications, signal.
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