283 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"L2CM" positions at Carnegie Mellon University
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As AI-enabled autonomous systems get closer to widespread deployment, fundamental research questions remain around their development and use, especially in high-stakes environments. How can we
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is fit for purpose and assists all student, alumni, faculty, and industry partners in the development of career education, career identification and search, and proactive pursuit of internship and
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Institute’s mission as a federally funded research and development center (FFRDC) sponsored by the U.S. Department of War. This position combines hands-on financial analysis with team leadership
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research and prototype capability development for government and DoW missions. This role spans the research-engineering spectrum: some SR MLRS hires may lean more research-heavy and others more engineering
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recommendations to our DoW sponsors, decision makers within government and industry, and at academic conferences. The SEI is a non-profit, federally funded research and development center (FFRDC) at Carnegie Mellon
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research and prototype capability development for government and DoW missions. This role spans the research-engineering spectrum: some SR MLRS hires may lean more research-heavy and others more engineering
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Robotics Institute at Carnegie Mellon. This position will be responsible for assisting in the development and execution of research projects, including experiment design, analysis of data collected and
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development center (FFRDC) at Carnegie Mellon University. What you’ll do: Develop state of the art approaches for analyzing robustness of AI systems. Apply these approaches to understanding vulnerabilities in
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development center (FFRDC) at Carnegie Mellon University. What you’ll do: Develop state of the art approaches for analyzing robustness of AI systems. Apply these approaches to understanding vulnerabilities in
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, and produce actionable recommendations. Prototype capability development: Build research prototypes, evaluation harnesses, and reference implementations that demonstrate feasibility and generate