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python), computational mechanics and fluid dynamics, numerical methods, machine learning, and the finite element method. In this position, the candidate will develop data-driven multiscale/multiphysics
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. We expect candidates to have substantial experience with statistical analysis and data management in R, Python, or Stata, as well as spatial analysis software. They are expected to bring particular
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language such as python and Unix-based operating systems such as MacOS or Linux. These tools are essential to set up, carry out, and analyze molecular simulation trajectories, and to interact with high
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-engineering skills, including experience with Fortran and Python and, preferably, C or C++, APIs, dynamic-link libraries, version control, Linux environments, and high-performance computing. The candidate
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experience in machine learning or AI; proficiency in Python and a deep learning framework; experience designing and evaluating computational models; and demonstrated scientific writing and collaboration
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experience in machine learning or AI; proficiency in Python and a deep learning framework; experience designing and evaluating computational models; and demonstrated scientific writing and collaboration
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environment on molecular design projects Skills with python, PyTorch and OpenMM programs Required Application Materials Cover letter CV Names and contact information for 3 professional references
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method. Proficient in python and C++ programming language. Special consideration will be given to candidates who are familiar with the open-source finite element library FeNiCS, brain finite element
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error correction codes and/or decoders for quantum error correction Experience with Python programming Experience with high-performance computing Experience with machine learning (theory and/or
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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