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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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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 26-May-25 Location: Boston, Massachusetts Type: Full-time Categories: Academic/Faculty Physical Sciences Internal
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Science Center and will work closely with PI Kathleen Lotterhos. NUMSC a strong research presence in evolution and ecology research and there are many opportunities for interaction and collaboration both
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of the nematode C. elegans. Our lab integrates genetics, live imaging, quantitative analysis, and computational approaches to uncover the molecular mechanisms regulating aging and longevity. Key Responsibilities
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multiple projects lead by the graduate students in the group and co-advise the graduate students. The candidate is expected to publish and present research findings in the computer science research
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structural engineering or architecture with a focus in computation. Key Responsibilities & Accountabilities (40%) Work with supervisor to develop a research topic and write a paper for conference or journal
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are specifically looking for candidates who possess a strong background in theoretical and computational modeling of biological systems, soft matter, or statistical physics. The positions will commence in January
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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 science
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the laboratory research team and may exercise functional supervision over supporting research staff. QUALIFICATIONS Ph.D. or equivalent required in Physics, Biophysics, Math, Chemistry, or Computer Science; be
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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