25 computational-physics "https:" "https:" "https:" Postdoctoral research jobs at Northeastern University
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· Assistive technologies for individuals with visual impairments · AI-driven physical therapy and rehabilitation systems · Human-robot interaction and coordination Responsibilities: Perform
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 15-Oct-25 Location: Boston, Massachusetts Type: Full-time Categories: Academic/Faculty Physical Sciences Internal
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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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of recommendation MINIMUM QUALIFICATIONS Candidates should have a Ph.D. in Physics, Mathematics, or Computer Science. A strong track record of research accomplishments in technical fields, ideally involving
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Julia), and Experience interacting with and communicating complex findings to diverse partners (e.g., the public, scientists, or public health officials). The hiring process for this role is ongoing
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information. We develop novel theoretical approaches to characterize the structure and function of the genome using the tools of statistical physics, information theory, and computational modeling
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proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. ● Pursue research topics such as protecting
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graduate students, and collaborate with clinicians and other collaborators of the lab. MINIMUM QUALIFICATIONS The candidate should have a PhD degree in biomedical/electrical engineering, computer
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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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such as mathematics, statistics, physics, computer science, engineering, epidemiology, or related disciplines; Strong background and experience in mathematical and computational modeling of infectious