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for the Modeling of Biological and Sociotechnical Systems (MOBS Lab) within the Network Science Institute at Northeastern University. MOBS Lab focuses on research projects aimed at developing innovative mathematical
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
/document/d/1C6tjLGrh45_k3EwcixMTrHMa_tB5LmWjjY1-GoE93rk/edit?tab=t.0 REQUIRED: A PhD in neuroscience, physics, applied mathematics, computer science, or a related field; excellent communication and teamwork
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influence the adaptability and evolvability of diploids and polyploids. Your profile You have a PhD in Computational Biology, Evolutionary Biology, (Bio)Engineering, Mathematics or Physics. You have expertise
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., encoder models, multi-modal embeddings, large language models), and mathematical modeling to map scientific concepts and their relationships, tracing how they change, merge, or diverge across time. Your
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 14-Apr-26 Location: East Lansing, Michigan Type: Full-time Categories: Academic/Faculty Mathematics/Statistics
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mathematical modelers and statisticians to perform data analyses. This work will include working with influenza viruses, rhinoviruses, and human coronaviruses. Responsibilities Include: Research- 75% • Perform
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to funder reporting Qualifications · Must have a PhD or equivalent in applied mathematics, statistics, biophysics, or similar. · Must be able to undertake full-time research and scholarship. · Must be able
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both mathematics and statistics and is highly research oriented. Additional information about the department may be found at https://www.math.msstate.edu . Requirements for a postdoctoral position
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beyond the department on new potential collaborations. Required Knowledge, Skills, and Abilities: PhD in nuclear engineering, experimental or theoretical low-energy nuclear physics or applied mathematics
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field (e.g., engineering, applied mathematics, statistics) Strong theoretical understanding and practical experience in machine learning, multimodal foundation models, continuous learning, and agentic AI