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Field
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on classical supercomputers. Design and optimize classical simulation algorithms for quantum circuits. Explore approximate classical simulation algorithms (e.g., tensor networks, circuit cutting) to improve
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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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(e.g., superconducting quantum processors). Validate, analyze, and interpret experimental data and results. Simulate the performance of quantum circuits on classical supercomputers. Design and optimize
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Bioinformatics expertise required for scRNAseq analysis. · Previous cell culture experience. · Perform molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental
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degree and experience in a relevant field. Ideal applicants will have experience in energy-system transition modeling, linear and mixed integer optimization programming, energy-related techno-economic
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, and optimize the REDCap database for large-scale electronic data collection, ensuring data quality and integrity. Train and supervise a team of Mental Health Consultants, research assistants, and
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to research projects, both independently and collaboratively. Sets up, maintains, and optimizes experimental equipment. Mentors and trains lab members in techniques and experimental design. Presents research
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probes. The postdoc will play a key role in designing and optimizing imaging devices, integrating hardware and software, and collaborating with a multidisciplinary team of clinicians, engineers, and basic
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presence at the Argonne campus in Lemont, Illinois. Preferred Qualifications: Experience in interdisciplinary collaborative research. Knowledge of large scientific code management and optimization. Job
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. Job tasks include optimizing intrinsic labeling systems (13CO2, 2H, 57Fe, etc.); developing high-throughput extraction, sample clean-up, and analysis methods for various plant foods and crops; analyzing