431 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"St" positions at Carnegie Mellon University
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machine learning methods. Technical Experimentation: You will experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains that include computer vision
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, working directly with Department of War (DoW) program offices and stakeholders to help them navigate complex technical, organizational, and acquisition challenges. This position emphasizes leadership
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What We Do: The SEI helps advance software engineering principles and practices and serves as a national resource in software engineering, computer security, and process improvement. The SEI works
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, working directly with Department of War (DoW) program offices and stakeholders to help them navigate complex technical, organizational, and acquisition challenges. This position emphasizes leadership
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Program Executive Offices (PEOs) and Program Management Offices (PMOs), sustainment organizations, contractors, and fleet stakeholders to ensure software solutions meet operational, maintainability, and
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program and potential for mentoring and advising undergraduates. All qualified candidates are encouraged to apply. This appointment requires teaching a Computational Linear Algebra for Data Analytics
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to perform clearly defined tasks with minimal direction Strong reasoning and problem-solving skills to build positive relationships Proficient computer and analytical skills. Qualifications: High School
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of experience, an MS with 8 years of experience, or a PhD with 5 years of experience in Computer Science, Electrical Engineering, or a related field. You’ve worked in a collaborative team environment as a
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eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions
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generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and experimental designs for large-scale cybersecurity research