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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 01-Mar-26 Location: Berkeley, California Type: Full-time Categories: Academic/Faculty Engineering Internal Number
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Nanomembranes and nanodevices Computational and data-driven modeling for nanomaterials discovery and design We encourage applications from scholars who apply interdisciplinary perspectives across a variety of
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Engineering, Computer Science, or a related field. Accompanying Knowledge, Skills, Abilities and Competencies Excellent abilities in molecular modeling and simulations (molecular dynamics or Monte Carlo
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The Theory and Modeling Group at the Center for Nanoscale Materials (CNM) seeks an outstanding Assistant Scientist to lead and support frontier research at the intersection of AI/ML, data
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of Distributed Mixture-of-Experts (MoE) and Small Language Models (SLMs) to create autonomous, intent-driven networks. This isn't just about connectivity; it’s about building a collaborative, agentic ecosystem
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service providers. Ability to work independently and collaboratively in a team environment. Ability to work in a high volume, deadline-driven, and results-driven environment. Preferred Skills, Knowledge and
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and domain adaptation for data-scarce regions and integration of weather, mobility, and socioeconomic data for predictive modeling. Distributed infrastructure resource management, including data-driven
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-organ models; high-content functional screening systems; biomedical digital twins; computational modeling of living systems; AI-driven physiological and pathological modeling; high-performance computing
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research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation
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software development. E3 Experience in training deep learning models relevant in research projects at scale. E4 Experience of applying good software engineering practices including but not limited