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. Close collaboration with our neighboring Departments (Mechanical Engineering, Electrical & Computer Engineering, Molecular Biology & Genetics, iNano, Biosciences, Food, Agroecology, and Chemistry) is a
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science, chemistry, electrical engineering or a related discipline Strong background in materials informatics and data science Proficiency in Python programming Experience in machine learning for materials
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at conferences and publish results in peer-reviewed journals. Support mentorship of junior researchers and/or students. Required Qualifications: PhD in Computational Organic Chemistry or Computational Materials
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integrate your code into their workflows. The preferred starting date is 1 December 2025. Profile You hold a PhD in Computer Science, Physics, Engineering or a discipline equally relevant to the topic
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molecular biological and quantitative techniques including microscopy, flow cytometry, computational/mathematical modeling, and utilizes approaches from synthetic biology and complex biological systems
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curious to deliver work that matters, your journey starts here! The Civil and Environmental Engineering Department at Carnegie Mellon offers a unique interdisciplinary program that enables you to develop
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Minimum Qualifications The candidate should have a Ph.D. in chemical engineering, mechanical engineering, chemistry, physics, or materials science with a computational modeling focus. Experience 0+ years
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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to a variety of structural biology problems relevant to biomedical research. The successful applicant will contribute to our synchrotron X-ray footprinting science and user support program. There will be
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. Shyam Kattel and will work within his research group. Kattel’s group focuses on a fundamental understanding of catalytic reactions on surfaces and interfaces by developing and employing computational