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in the field of network science, with applications to nutrition, biological networks, network medicine, and the science of science. The position involves developing and applying computational
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, computer science, mathematics, or statistics or related field. The BarabásiLab is seeking motivated individuals with an interest in exploring complexity and its applications to food, art, science, and medicine from
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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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existing and new computational methods to study multiscale processes in catalysis and photochemistry. Other projects that align with our general interest are also possible. Please see https://sdonglab.org
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-world problems in the fields of Biology, Health, and Engineering. An effective research program will execute use-inspired discovery with an entrepreneurial mindset that develops science and solutions
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Halverson. The successful candidate is expected to contribute to the scientific mission of the collaboration, bringing their technical expertise to bear on problems in AI. Proposals for new scientific
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: Provides scientific and technical leadership in the management, design, and conducting of the entire research program in resilient AI within Prof. Restuccia’s research group. Responsibilities include
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, the college collaborates across the university, the Northeastern network, and partners around the globe. The Writing Program at Northeastern University, housed in the College of Social Sciences and Humanities
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the supervision of Prof. James Halverson. The successful candidate is expected to contribute to the scientific mission of the collaboration, bringing their technical expertise to bear on problems in AI. Proposals
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to join the SoundMind Collaboratory and Brain Game Center for Mental Fitness and Well-being at Northeastern University. Together Seitz and Jaeggi have a broad research program that takes a lifespan approach