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matrix theory, statistical inference, active matter, and biophysical modeling are desirable. Special Instructions Letters of recommendation are required at the time of application. Candidates should submit
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rolling basis. The position will remain open until filled. Basic Qualifications A Ph.D. in Mathematics, Applied Mathematics, Computer Science, or a related field, by the start of the appointment. Additional
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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cse-lab.harvard.edu . Basic Qualifications: Doctoral degree. Applicants background may include studies in: Computational Science, Computer Science, Applied Mathematics, Engineering and Physics
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to study design and appropriate statistical methods, manage and maintain documentation of files and analyses. This person will summarize and present findings as reports, tables, graphs, and models, and will
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. Basic Qualifications: Applicants should have least 2 years of directly applicable postdoc experience Additional Qualifications: Prior experience with random matrix theory, statistical inference, active
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, such as competition, management, and innovation. Research often draws heavily on applied econometrics and microeconomic theory. These positions are ideal for candidates with an interest and plans
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of nanoparticles and metals, ARDS), James P. Butler (physics, applied mathematics, sleep, respiratory mechanics), Philip Demokritou (effects of nanoparticles on biological systems, nanoscience, aerosol engineering
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will work on campus. Basic Qualifications Bachelor’s degree in the quantitative sciences such as: Computer Science, Economics, Statistics, Mathematics, Physics, Political Science (or other Quantitative
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rolling basis. The position will remain open until filled. Basic Qualifications A Ph.D. in Mathematics, Applied Mathematics, Computer Science, or a related field, by the start of the appointment. Additional