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for peer reviewed publications Qualifications*Ph.D. in Environmental/Civil Engineering, Computer Science/Engineering, Data Science, or a closely related field*Proficiency in Python or other tools and ML
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at Princeton University.We welcome applications from all areas in mechanical and aerospace engineering, including but not limited to the fields of: Bioengineering Combustion and Energy Science Computational
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related field (e.g., statistics, computer science, electrical engineering, applied mathematics, or operations research) before May 2025 are encouraged to apply. Ideal candidates will display outstanding
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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senior ranks may have multi-year appointments. A PhD is required, with appropriate research experience in quantitative biology, (bio)physics, (bio)engineering or related Engineering and Physical sciences
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the Department of Chemical and Biological Engineering to study the biochemical and mechanical mechanisms that define pattern formation during branching morphogenesis of the lung and mammary gland. Further
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expertise and proficiency with net-zero systems thinking, experience with a variety of programming languages, and familiarity with critical path planning tools, are essential. A Ph.D. in engineering
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quantitative and computational social science, addressing a diverse array of new data and analytic challenges, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation
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the guidance of Dr. Arash Adel, Assistant Professor in the School of Architecture and Associated Faculty of the Department of Computer Science. The desired start date is Spring 2025. Appointments are for one
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are sought. Applicants will have an engineering PhD, or equivalent degree and experience in a relevant field. Ideal applicants will have experience in energy-system transition modeling, linear and mixed