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Strong domain knowledge in one or more technologies and capabilities relevant to APEX (e.g. Statistical signal processing, artificial intelligence, machine learning, mission planning, autonomy.
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We are passionate about incorporating the latest technologies in computer vision, image processing, computational photography, machine learning and artificial intelligence into todays most advanced products: smartphones, tablets, PCs, and greatly improve the consumer experiences.
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Essential Functions Numerical simulations and/or numerical modelingExperimental data analysisCoding (Matlab and/or Python and/or Fortran)Presenting research resultsWriting manuscripts Education & Experience Education: PhD Previous Experience Desired: Ocean acoustics and/or acoustical signal processing and/or ocean numerical modeling and/or inverse methods and/or machine learning.
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Work collaboratively with data scientists, machine learning engineers, and DSP engineers to create, execute, and execute test plans, both in simulation and as implemented on embedded products, to identify areas of improvement and validate expected functionality of video and audio signal processing, machine learning, and artificial intelligence.
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Mixed-Signal IP Machine Learning Engineer. Develop machine learning models and systems to optimize the Power, Performance, Area, and Robustness (PPAR) of mixed-signal IPs.
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Your expertise in machine learning will be instrumental in optimizing Power, Performance, Area, and Robustness (PPAR) in our mixed-signal IP development. Knowledge of signal processing is a plus.
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Advanced knowledge of clinical research, signal processing, time series analyses, EEG/ECoG/iEEG, advanced statistics, Python, brain stimulation therapies, neural modelling, biomarker development, and brain stimulation and recording techniques.
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Our mission is to push the envelope in Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing, in order to provide the best-possible experience for our customers.
$159,100 - $309,400 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience with hardware, software integration, EO/IR, passive and active radar integration, digital signal processing, and with in-field testing and validation of systems. and machine learning software implementation using machine learning libraries, including TensorFlow, Pytorch, or Keras.
$110,100 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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These algorithms span a wide range of product facets, from machine learning algorithms that drive the core life-saving functionality of our wearable devices to field data analysis algorithms that provide critical insight into product usage, patient experience, potential improvements, and new products.
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3+ years' experience in wearable sensor technologies (e.g. capacitive, inertial, optical, EMG), signal processing, machine learning, or related areas. We are specifically looking for a candidate with broad knowledge of sensor design, sensor fusion, state estimation, signal processing & modeling, machine learning algorithms, and who can implement this knowledge in software to drive progress in next-gen AR/VR human-computer-interaction research.
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3+ years of direct experience in Machine Learning, Computer Vision, Signal Processing, or Natural Language Processing (NLP) Use statistical and machine learning techniques to create scalable solutions for vehicle telemetry data and video analysis, and perform R&D to drive discovery of new generation mobility products.
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With experience in Field Programmable Gate Array (FPGA) design as it relates to digital signal processing (DSP), radar, communications and EW systems, you will be expected to contribute on current programs and quickly grow into a task leader.
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KRI headquarters, located at the NU Innovation Campus in Burlington, MA (ICBM), is home to one-of-a-kind research and test facilities for conducting activities related to cognitive and distributed RF signal processing and machine learning, unmanned and autonomous system technologies, as well as quantum materials and sensing.
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As a Senior Machine Learning Research Scientist, you will apply your technical skills to a variety of exciting programs and datasets, primarily focused on remote sensing applications (acoustic, RF, and other.
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