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Advanced Quantum Testbed Project Scientist AM-Applied Mathematics and Computational Research. Berkeley Lab’s Applied Mathematics and Computational Research Division (AMCRD) has an Advanced Quantum Testbed Project Scientist position to join its Advanced Quantum Testbed (AQT) program.
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BS or MS in Computer Science, Computer Engineering, Applied Mathematics, Electrical Engineering or related field. Experience with algorithm optimization for real time systems, especially radar or remote sensing.
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A Ph. D. in Electrical Engineering, Data Science, Computer Science, Applied Mathematics, Mathematics, Machine Learning, Artificial Intelligence, Software Engineering, or related field is required.
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Bachelors degree in Engineering, Physics, Applied Mathematics, or other related field. MA/MS in Engineering, Physics, Applied Mathematics, or related field. Background in image and signal processing, both algorithm design and implementation.
$100,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Education: Master’s degree or above in biomedical, applied mathematics, computer science, engineering, or related areas. Knowledge of algorithm optimization for embedded systems.
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We are looking for applicants with an interest and background in algorithm development, applied engineering, prototype development and testing, and modeling and simulation to support the development and implementation of safety critical systems that will enable the integration of increasingly autonomous systems into the transportation system.
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MS or Ph. D. in chemical engineering, data-science, operations research, applied mathematics, statistics, or other relevant fields. In this role, you will develop and deploy computational models for ArkOS spanning (1) advanced real-time data capture (e.g., real-time state estimation based on spectroscopy data), (2) operational digital-twin simulations (e.g., enabling robust hybrids models of cell growth and other critical parameters), (3) model-based control (e.g., deploying supervisory control algorithm for batch optimization.
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Masters or Bachelors in Physics, Computer Science, Applied Mathematics, or Electrical Engineering. Knowledge of discrete mathematics, numerical analysis and scientific computing techniques.
$96,800 - $118,600 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Applied mathematics or algorithm development experience. In particular, RMS provides expertise in the discovery, modeling, and mitigation of failures due to extrinsic radiation and reliability degradation in advanced technologies operating in harsh environments space, terrestrial, military, or commercial through radiation effects analysis, IC modeling and simulation (M&S), IC testing, and radiation-hardened IC design.
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BS degree in Engineering, Computer Science, Applied Mathematics, Statistics, or related field, plus 5+ years of experience in program management; IERUS specializes in technology research, testing, and implementation with core competencies in electromagnetics phenomenology, computational analytics (algorithm acceleration and machine learning), and weapon system engineering.
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3+ years of work experience or equivalent in highly quantitative field, such as data science, applied economics, applied statistics, mathematics, or physics. Develop and deepen Subject Matter Expertise in Fair Lending and Fairness regulations/laws as it relates to algorithm review through internal, external, and on-the-job training.
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Java, MatLab, or other) Undergraduate degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline Desired Skills: Agile Scrum Git/Gitlab - source code versioning Jira - issue tracking and agile project management Algorithm implementation Multi-core and multi-threaded C.
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Ph. D. in Applied Mathematics, Physics or Engineering with a focus on computational sciences, Computer Science or related area. The Applied Sciences Laboratory at SRI International is seeking multiple Applied and Computational Scientists to conduct research and development in the areas of mathematics of generative AI models, scalable graph analysis methods and network sciences, uncertainty quantification and rare event prediction methods, and quantum computation.
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A Ph. D. in a field that’s at the heart of our work, like Machine Learning, Computer Science, or Applied Mathematics. Keywords: Dexterous Manipulation, Robotic Manipulation, Reinforcement Learning, Imitation Learning, Robotics, Machine Learning, Python, PyTorch, TensorFlow, ROS2, Algorithm Development, Sim-to-Real, Continual Learning, Large-Batch Simulations.
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What We Need to See:A minimum qualification of a Master's degree (or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields. Ways to Stand Out From the Crowd:Published research or noteworthy contributions to the field of deep learning, particularly around algorithm development for efficient deployment at scale.
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