156 coding-"https:"-"FEMTO-ST"-"CSIC" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "St" positions at Carnegie Mellon University
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computing, you will identify, shape, apply, conduct, and lead research in support of critical U.S. government needs. The ideal candidate will have a strong background with hands-on experience in one or more
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online testing of the planner in different operational configurations Conducting extensive simulation testing of the planner in a variety of uncommon configurations Documenting the code and supporting
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, uncertainty and calibration approaches, and repeatable test pipelines. Engineering rigor appropriate to the task: Write clear, maintainable code and documentation with a level of engineering discipline
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Reverse Engineer Researcher for the Threat Analysis directorate. The SEI is a federally funded research and development center at Carnegie Mellon University. What you’ll do Reverse engineer malicious code
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curious to deliver work that matters, your journey starts here! In a region booming with opportunities, CMU is the only U.S.-based research university offering its master’s degrees with a full-time faculty
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, uncertainty and calibration approaches, and repeatable test pipelines. Engineering rigor appropriate to the task: Write clear, maintainable code and documentation with a level of engineering discipline
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-aided control of manipulators on mobile robots for real world applications Prototyping in scripting languages Transitioning applications to deployment with production quality code Designing, developing
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that delivers timely and high-quality results. We’re looking for a creative engineering student to design and develop software prototypes, find weaknesses in source code and research methods for software
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malicious code in support of high-impact customers, design and develop new analysis methods and tools, work to identify and address emerging and complex threats, and effectively participate in the broader
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; comfortable developing production‑grade code and APIs. Solid understanding of ML theory, statistical learning, and common algorithms. Hands‑on experience with TensorFlow, PyTorch, Torch, Caffe, or similar deep