398 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" uni jobs at Carnegie Mellon University in United States
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models such as GPT and LLaMA, designing and deploying agentic workflows, as well as apply and advance traditional ML research and engineering across domains such as natural language processing, computer
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Systems (S3D) is one of the seven academic departments of the Carnegie Mellon School of Computer Science (SCS). S3D hosts the SCS PhD programs in Software Engineering (SE) and Societal Computing (SC), along
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following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing (HPC
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curious to deliver work that matters, your journey starts here! The College of Engineering at Carnegie Mellon is a world-class engineering college recognized for excellence, innovation, and the societal
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, sensors and sensor fusion, planning, computer vision, or related areas. In addition, you have demonstrated applying systems engineering principles and collaborated across multi-disciplinary project teams
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laboratory technician to play a key role in detector development for high-energy physics experiments. Learn more about this exciting department at https://www.cmu.edu/physics/research/nuclear-particle.html
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, knowledge‑sharing, and supportive collaboration Required Qualifications: Bachelor’s degree in Computer Science, Engineering, Physics, or a related technical field At least 3 years of experience developing
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What We Do At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of Artificial Intelligence
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, computer vision, time series forecasting, and other predictive analytics. You will collaborate closely with senior researchers, software engineers, and government sponsors to define problem statements
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models such as GPT and LLaMA, designing and deploying agentic workflows, as well as apply and advance traditional ML research and engineering across domains such as natural language processing, computer