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Field
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Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances
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marketing scholarship. The appointment is one year with the possibility of a second-year renewal contingent on performance in the first year. The postdoc will manage the Jeff Conant Behavioral Lab as a shared
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; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding. POSITION
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physics software and high-performance computing (HPC). These include particle and gravitational physics. -On the data analysis side, the group designs novel statistical methods for particle physics and
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application to energy systems applications Hands-on experience with JuMP.jl or similar algebraic modeling languages (e.g., Pyomo, GAMS, AMPL). Familiarity with high-performance computing (HPC) environments
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, single cell and multi-omics data analysis, and a high-performance computing environment (Unix/Linux) is highly preferred. An individual with Next generation sequencing experience is preferred. A good
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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addition to the duties specified, the Postdoctoral Associate will serve as Coordinator for Department of History’s History+ program in summer of 2027. Additional compensation will be included for this work performed. The
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Synthesis Science program in which the postdoc will combine literature data extraction, LLM reasoning, and theoretical materials science to guide synthesis protocols for automated sol-gel and solid-state
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quantum transduction and terahertz (THz) photon generation via enhanced light–matter interactions. The postdoc will lead efforts in device patterning and the integration of complex materials—such as