50 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at Northeastern University
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institute and would be encouraged to find ways to thrive and grow their own research program. This position is Boston-based and is available through grant funding that runs until August 31, 2026
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collaborates with faculty, students, and external partners to translate rigorous methods into practical tools. QUALIFICATIONS: Ph.D. in Applied Mathematics, Electrical & Computer Engineering, Computer
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to translate rigorous methods into practical tools. QUALIFICATIONS: Ph.D. in Applied Mathematics, Electrical & Computer Engineering, Computer Science, Industrial Engineering, or a closely related field by start
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aspects of data science. This position will focus exclusively on research and will not have teaching or service obligations. The successful candidate will devise and conducting numerical experiments
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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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About the Opportunity Job Summary The Copos Group works on computational and mathematical theoretical models with direct applications to several open problems in cell biology. We are specifically
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. The research focus will be on developing and applying first-principles-based and data-driven computational methods to understand multiscale processes and to accelerate chemical discoveries for renewable energy
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the supervision of the PI, including proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. Pursue research topics
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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determinants of health with a focus on cognitive decline/dementia and an emphasis on the application of epidemiologic, econometric, and other methods to strengthen causal inference using multilevel, longitudinal