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deep expertise in modern machine learning and a strong record of research accomplishment who are excited to advance foundation models, agentic systems, and new AI approaches for high-impact scientific
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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analytics, including correlation analysis and machine learning techniques. Preferred Qualifications: Experience with microstructure characterization techniques (SEM, EBSD, TEM, XRD). Experience in mechanical
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opportunities to develop scientific independence, establish new research directions, collaborate across disciplines, mentor junior scientists, and acquire the skills and publication record necessary for the next
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Intelligence and Machine Learning. Join a team of scientists at the leading macromolecular crystallography beamlines and at the computing center and contribute to science projects at the interface between AI
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groups from Stanford and beyond working on complementary approaches to T cell recognition. Our group provides an intellectually rich environment, with scientists applying genetics, proteomics and machine
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Type of Position Temporary Position Time Status Full-Time Required Education PhD, DrPH, or other doctoral degree in public health, sociology, psychology, or similar field completed within the past five
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the Principal Investigator (Dr. Shengli Zou). Conduct advanced computational chemistry research with a focus on nanophotonics, quantum mechanics, and machine learning–assisted modeling and simulations. Prepare
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Requisition Id 16802 Overview: We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations, and machine learning (ML) methods relevant
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret