10 programming-"https:"-"https:"-"https:"-";" Postdoctoral positions at Michigan State University
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Computer programming skills Desired Qualifications Experience developing computational tools for biomolecular systems Experience training machine learning models Experience working in a collaborative
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independently Confidence with computational biology including use of programming languages such as R, python and some familiarity with high performance computing Excellent communication and interpersonal
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methods to biological systems Proficiency in Python programming Excellent written and verbal communication skills First-author peer-reviewed publication(s) Desired Qualifications Experience
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ultrasound, wearable and accelerometry-derived loading or physical activity analytics, gait biomechanics, or circulating biomarker analysis. Programming proficiency in R, Python, or MATLAB. Experience with
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programming skills Desired Qualifications Experience developing computational tools for free energy calculation Experience developing containerized workflows Experience working in a collaborative
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integrating geophysical data with groundwater or vadose zone models Familiarity with irrigation systems and agricultural water management Programming experience (e.g., Python, MATLAB, R) for data analysis and
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Qualifications Experience programming in C++ Experience in using ROOT and Geant4 Experience in nuclear electronics and data acquisition Experience in detector design and assembly Required Application Materials
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partnerships and programming, research incubators, and mentorship. As an institution of higher learning, Michigan State University is committed to providing a safe environment for its students, faculty, and
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software(s), proficient in programming in both R and/or Python. Ability to collaborate and clearly communicate with stakeholders, state and federal agency biologists, university scientists, and non
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Python and R programming for statistical modeling, data visualization, and integration of large-scale genomics datasets Participate in the design of strategic data acquisition plans to support ongoing