455 computational-physics-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Carnegie Mellon University
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of International Education, EM Marketing & Communications and Enrollment Systems. Collaborate with strategic campus partners such as Institutional Effectiveness & Planning, Computing Services
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& statistical mechanics, and topology. Familiarity or expertise in formalization and computer-aided reasoning in mathematics is an added plus. Exceptional candidates in all areas will also be considered. In
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challenges. Requirements: Enrolled in a degree granting program. Willingness to travel to various locations to support the SEI’s overall mission. This includes within the SEI and CMU community. You will be
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The Carnegie Mellon University Department of Athletics, Physical Education and Recreation will have a transformative impact through multicultural programs that inspire leadership, collaboration
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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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, or presentation; writes technical reports. May build and validate quantitative models. Identifies problems and obstacles to progress; develops strategies to solve problems. May program software in support of job
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for the Pitkow Lab. Core Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments
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technology research, such as AI, computer science, engineering and robotics, CMU is now poised to strengthen its support and commitment for innovators and founders across all domains. During its first decade
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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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Responsibilities Design, implement, and evaluate state‑of‑the‑art ML models (computer‑vision, NLP, planning, etc.) using frameworks such as TensorFlow, PyTorch, Torch, or Caffe. Build and maintain robust data