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                on superconducting QPUs. Knowledge of noise and error sources in superconducting systems. Familiarity with benchmarking and characterization methods for quantum computers. Experience with tensor network methods and 
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                • Demonstrated experience in computational or quantitative research methods. • Strong programming skills in Python. • Experience with high-performance computing, geospatial data, and causal inference methods 
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                oral communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs 
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                to define novel questions and methods for leveraging available economic, biological, and environmental data, and communicating the research through publications. The Postdoctoral Researcher will have 
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                collaborate with research partners to develop and utilize novel characterization and diagnostic methods to identify critical performance and durability barriers for these electrochemical devices and develop 
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                programming skills are essential, along with a track record of published papers and strong self-motivation. - Prior experience in the areas of machine learning / data-driven methods, signal processing and/or 
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                or papers from Ph.D. currently under review Experience with life-cycle costing, life-cycle environmental assessment methods and/or software Strong skills in Python (preferred) and/or a similar programming 
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                -motivation. - Prior experience in the areas of machine learning / data-driven methods, signal processing and/or applied mathematics. The position is for one year with renewal for a second year pending 
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                information science, and applied social science research. This position is well-suited for someone interested in research design and the application of geographic principles and methods to policy analysis and 
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                the group are encouraged to develop new data analysis ideas and methods. The successful candidate will also be heavily involved in our ongoing project to develop and build new, high-speed data acquisition