12 parallel-processing-bioinformatics-"https:" research jobs at Lawrence Berkeley National Laboratory
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implementing, optimizing, or integrating quantum libraries such as Itensor, CUDA-Q, Qiskit, or PennyLane. Experience debugging and profiling distributed-memory parallel applications. Knowledge of Git and modern
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distributed-memory parallel applications. Experience with containers (Docker, Podman, Shifter or similar) and modern software practices such as Git, unit testing, CI/CD, and collaborative development
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detection, with a strong emphasis on applications in experimental searches for new physics. This role is hosted in the Quantum Measurement Group (https://quantum-measurement.lbl.gov/ ), and supervised by PI
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-tuning and/or Retrieval-Augmented Generation (RAG) methods to augment LLMs with dedicated knowledge in transportation and electric grid domains. This involves designing methods to process input data and
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of Advanced Quantum Testbed (AQT) and Quantum System Accelerator (QSA). This position will focus on design, calibration, and operation of mid-scale digital superconducting quantum processors. These processors
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prepared to provide documentation during the clearance process. Required Application Materials: Curriculum Vitae Cover Letter - Briefly describing the candidate's background, previous research experience as
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accessible gate-based quantum computer. Our technology platform is based on superconducting quantum circuit processors, and we aim to generate the detailed experimental findings needed to resolve foundational
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experimental tools to investigate chemical and mechanical processes that contribute to the enhanced reactivity of minerals in sedimentary formations. Your role will be to lead the design, implementation, and
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-stack quantum processing units (QPUs). Develop and validate performance bounds for QPUs beyond brute-force classical simulability. Design and conduct experiments on contemporary quantum hardware platforms
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quantum computer control systems. Assist in developing and testing PCB boards. What is Required: Ph.D. degree in physics, applied physics, electrical engineering, or a related field within the last 3 years