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methodologies generally, machine learning techniques, OR complexity analysis/nonlinear dynamics are particularly well-matched to the opportunity, but applicants with theoretical expertise related to compact
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methodologies generally, machine learning techniques, OR complexity analysis/nonlinear dynamics are particularly well-matched to the opportunity, but applicants with theoretical expertise related to compact
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and observational data from space-borne missions (most notably Kepler and TESS); be proficient in computational astrophysics, astrostatistics, and/or exoplanetary science; participate in Departmental
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and observational stellar astrophysics, computation astrophysics, astrostatistics, and/or exoplanetary science. Teach 2 sections of the Mendel core science courses or labs per semester (currently “How
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of Engineering with many fascinating projects that focus on applying advanced nonlinear theoretical, computational and experimental techniques to solve practical real-world problems in engineering and biomedicine