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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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/fractionalized phases of matter, via computational many-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating
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Postdoc Appointment Term: 2 year renewable Appointment Start Date: As early as summer 2025 Group or Departmental Website: http://www.staarlab.com (link is external) How to Submit Application Materials
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University of California, San Francisco | San Francisco, California | United States | about 6 hours ago
supervises a team of 3+ direct reports and temporary support employees, and works with 160+ employees department (Organized Research Unit – ORU), which includes faculty, postdocs, affiliates (including
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, or a related field) A relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) Strong skills in machine
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preferred but not required. ? The prospective applicant does not have to be an expert in localization. However, good knowledge of wireless communications, digital signal processing, and computer algorithms
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Qualifications ? Ph.D. in Physics, Materials Science, or a related field with a concentration in electron microscopy methods ? Experience in the collection and processing of TEM/STEM data ? Computer programming
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. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We expect you to be able
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related discipline. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We
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research teams that include faculty, graduate students, and undergraduate students. One student’s research used machine learning to solve physics problems, while another’s helped create a data science