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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 months ago
Organization National Aeronautics and Space Administration (NASA) Reference Code 0146-NPP-JUL25-ARC-EarthSci How to Apply All applications must be submitted in Zintellect Please visit the NASA
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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in soil processes, plant physiology, plant traits, and species composition Strong data analysis skills, including proficiency in R or Python coding, and/or machine learning techniques Excellent writing
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and other machine learning models (especially neural network models, time-series models) and coding in python and R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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applying data science principles and techniques to biomedical datasets. Applicants should be comfortable using coding skills such as SQL, R, and Python to extract data from databases, clean it, and analyze
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coding/scripting (e.g., R, Python) as evidenced by application materials. NOTE: To be appointed at the Postdoctoral Researcher title, it is necessary to have the PhD in hand. Appointments made without a
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with electronic health record (EHR) and/or clinical data. Proficiency in Python, with strong coding and debugging skills. Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow
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, robust, and reproducible data analysis. Conventional statistical approaches will be combined with innovations in interpretable machine learning to address each aim from multiple angles. Analysis code will
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mathematical algorithm in codes and work on submitting papers Analyze theoretical and numerical results, summarizing findings in reports. Write and submit papers for publishing in peer-reviewed journals and
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Organization U.S. Department of Energy (DOE) Reference Code DOE-OREM-ESPSE-24 How to Apply A complete application consists of: An application Transcripts A current resume including academic history