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We're seeking candidates with expertise in two or more of the following areas: RF/radar signal processing, optimization, electronic warfare, machine learning, adaptive signal processing, algorithm development, test & evaluation, model & simulation, or systems engineering.
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Should have a strong background in at least two of the following areas: Algorithm Development, Machine Learning/AI and Data Analysis, Mathematical Modeling and Simulation, Digital Signal Processing, Control Algorithms Design.
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The ISR Division’s projects focus on advanced signal processing, adaptive sensor technologies, advanced algorithms, machine learning, and modeling and simulation for applications that include airborne radar, electronic warfare, and undersea systems.
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Deep knowledge or experience with digital signal processing filters design, analog-on-top mixed signal physical and timing interface implementation techniques, and a passion to pursue out-of-the-box physical implementation techniques to achieve uncompromised design goals.
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Design and apply cutting-edge signal processing and machine learning techniques to solve complex radar and RF sensing and counter-sensing challenges such as signal detection, classification, autonomous sensor decision-making, radar, electronic warfare, waveform design, electronics support measures, and more.
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We are looking for students who are self-motivated and interested in signal/image processing, machine learning, deep learning, statistical pattern recognition, and high-performance computing.
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Massachusetts General Hospital (MGH) Department of Neurology and Harvard Medical School (HMS) is seeking a signal processing and machine learning post-doctoral fellow for a full-time position in the Gupta Lab. The fellow will be applying diverse methodologies to uncover information in multimodal data collected from individuals with common and rare neurodegenerative diseases.
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This includes the following: - Crafting sophisticated layout for mixed signal and analog circuits in deep sub-micron CMOS technologies. Proven experience in analog/mixed-signal layout design of deep sub-micron CMOS circuits.
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Proficiency in one or more of the following areas: RF circuit design and troubleshooting, software defined radios (SDRs), digital signal processing (DSP), electromagnetic propagation, or types of RF and Microwave antennas.
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The team leverages its experience in the fields of signal processing, computer vision, computational linguistics, machine learning, artificial intelligence, communication systems, and other areas of electrical engineering and computer science to create impactful solutions.
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For embedded systems You have proficiency in radar signal processing techniques, DSP algorithms, and the entire ML lifecycle Familiarity with radar principles, systems, and waveforms.
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Develop and implement deep learning models to predict and optimize enzymes and metabolic pathways in microbial systems. Ph. D. in Bioengineering, Biochemistry, Biostatistics, Chemical Engineering, Computer Science, or similar discipline, with 0-5 years of experience and a strong focus on deep learning and/or cell engineering.
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Strong understanding of digital signal processing (DSP) and RF systems. Background in wireless communication systems (OFDM/CDMA) or radar signal processing. Develop and optimize digital signal processing (DSP) algorithms for FPGA implementation.
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Advanced coursework or extensive job experience in digital signal processing, with a focus on algorithm development, optimization, and implementation. Digital Signal Processing (DSP.
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The successful candidate will have demonstrated leadership skills and expertise in areas such as: RF, radar, communications systems, analog and digital signal processing, software-defined radios (SDRs), FPGA firmware and hardware development, microcontrollers and embedded processors, physics modeling and simulation, systems engineering, and test & evaluation.
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signal processing deep learning jobs Title: engineer systems Company: Leidos in Woburn, MA
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