15 parallel-computing-numerical-methods-"https:" research jobs at Lawrence Berkeley National Laboratory
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communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs. Experience
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tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics, or a related numerical field. Programming experience
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projects. Hands-on experience with state-of-the-art experiments on contemporary quantum hardware platforms. Experience with numerical algorithms (e.g., tensor networks) for simulating quantum computer
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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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Mathematics Computational Research Division (AMCR) has an immediate opening in the Quantum Information Science and Technology Group (QuIST) for a Quantum Experimentalist Postdoctoral Fellow under the programs
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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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the fundamental mechanisms of mineral interfacial chemistry, element and isotope partitioning, crystal growth, dissolution, and phase transformation. The project team uses state-of-the-art computational and
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theorists and experimentalists; mentor interns and junior researchers. Champion safety & cybersecurity in all collaborative and computational activities. What is Required: Ph.D. in Chemistry, Physics
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experimental data. Apply modern methods of machine learning towards predictive data analysis. Collaborate with other research teams and scientists. Publish original research in peer-reviewed journals and
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stability and performance in nanoscale materials for microelectronics. You will measure interfacial thermal conductance in 2D material systems using advanced optical methods such as time-domain