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functional theory) and high-performance computing. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to
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., epidemiology, applied mathematics, statistics, or network science) by the start of the appointment, Experience developing complex models for real world data, with strong programming skills (R, Python, and/or
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., epidemiology, applied mathematics, statistics, or network science) by the start of the appointment, Experience developing complex models for real world data, with strong programming skills (R, Python, and/or
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disease dynamics, preferably with applications to emerging or re-emerging diseases; Proficiency in programming languages such as R, Python, MATLAB, C++, or similar tools for data analysis and model
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data visualizations using common libraries like D3.js, ggplot, or vega, as well as expertise in languages and libraries for data analysis such as R or Python. Lastly, candidates should have experience
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. Programming skills (Python or Fortran preferred, but not required) are desired. Experiences with catalysis (biological, homogeneous, or heterogeneous), excited-state simulation methods, multiscale simulations
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of the Postdoctoral Research Associate includes contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will
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lab Director Dr. Neha P. Gothe. The position involves working on multiple projects in an active research laboratory. The candidate will work with an interdisciplinary research team. The candidate will
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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manipulation, and agroinfiltration; Strong record of high-quality publications in related scientific fields; Excellent communication, teamwork, and problem-solving skills; and Ability to handle multiple tasks