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About the Opportunity SUMMARY Northeastern University invites applications from outstanding candidates to fill one or more Postdoctoral Research Associate (PRA) positions in computational quantum
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of computational materials discovery starting in Summer 2025 . Our group is seeking to discover novel materials for renewable energy applications using high-throughput quantum chemistry calculations and data-driven
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of computational materials discovery starting in Summer 2025. Our group is seeking to discover novel materials for renewable energy applications using high-throughput quantum chemistry calculations and data-driven
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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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. Postdocs also have opportunities to work with Northeastern’s centers for student and faculty advancement, including the Writing Center, PhD Network, Digital Integration Teaching Initiative, Center
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://tanglab.sites.northeastern.edu/ Qualifications: Having a PhD degree from all science and engineering majors, especially Mechanical Engineering, Chemical Engineering, Physics, and Materials Science. Highly motivated. Having
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previous experience; ability to write papers for peer-review on technical topics related to architectural design and machine learning and conduct grant research; as normally acquired through a PhD in
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to assist in the precise diagnosis of major diseases, including cancer and cardiovascular disease. QUALIFICATIONS: PhD in Electrical Engineering, Applied Physics, Biomedical Engineering, or a relevant field
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biomedical imaging system to assist in the diagnosis of widespread diseases, including cancer. QUALIFICATIONS: PhD in Electrical Engineering, Applied Physics, Physics, or a relevant field. Demonstrated
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to collaborative projects that explore the intersection of complex systems and public health. Qualifications PhD in a related discipline (e.g., epidemiology, applied mathematics, statistics, or network science) by