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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 03-Oct-25 Location: Berkeley, California Categories: Academic/Faculty Internal Number: 105303 Lawrence Berkeley
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Lawrence Berkeley National Laboratory - Physics | Berkeley, California | United States | about 1 hour ago
94720, United States of America [map ] Subject Areas: Physics / Quantum Sensing , HEP-Phenomenology (hep-ph) , hep-th , High Energy Physics , High Energy Theory , Particle Physics Appl Deadline: 2025/11
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research into control theory of neural population dynamics. This position has the specific focus of developing ML methods to assess the feedback controllability of neural population dynamics recorded from
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theory & experiment: Co‑design validation experiments with experimentalists; iterate models using feedback from new measurements. Automate the workflow: Build Python workflows for simulation and data
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 21-Sep-25 Location: Berkeley, California Categories: Academic/Faculty Internal Number: 105193 Lawrence Berkeley
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the components of a system permit the continuous regeneration of these same components. Because of the history of this subject, we are especially interested in candidates with an expertise in category theory
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 31-Aug-25 Location: Cambridge, Massachusetts Categories: Academic/Faculty Other - Academic/Faculty Internal Number
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 26-Sep-25 Location: Berkeley, California Categories: Academic/Faculty Internal Number: 105249 Lawrence Berkeley
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Qualifications: Experience in one or more of the following areas: quantum sensing, theory development aimed at experimental searches for new physics, and foundational knowledge of particle physics. The posting
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integral equations Machine learning, especially the areas of optimization, learning theory, probabilistic modeling, deep learning, and high dimensional data analysis, as well as applications of scientific