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completed all requirements for a PhD program (or equivalent) except the dissertation in ecology, environmental science, or a closely related discipline at the time of application Additional qualifications
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Lawrence Berkeley National Lab’s (LBNL ) Accelerator Technology & Applied Physics (ATAP ) Division’s Berkeley Accelerator Controls and Instrumentation (BACI) Program has an opening for a
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to provide a full-time training program of advanced academic preparation and research training under the mentorship of a faculty member. Applications are welcome from all areas of theoretical physics, broadly
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to these values. A variety of resources and programs are available to academics, staff, and students that reflect the core values reflected in our strategic plan: “To Boldly Go,” our Principles of Community
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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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reviews or reports. Proficiency with Python-based scientific programming tools. Desired Qualifications: Knowledge of superconducting qubits and device physics. Experience with gate calibration
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, ranging from underground searches, accelerator experiments, CMB observations, to strong and weak gravitational lens probes. Specifically, the successful candidate will drive a program of comprehensively
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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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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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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial