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transformative AI projects. MINIMUM QUALFICIATIONS Expert knowledge of at least one major cloud platform (AWS, GCP, or Azure) Strong programming skills in Python and infrastructure-as-code tools Proficient with
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limited sample proteomics is highly desirable. Knowledge of R or Python coding would be desirable but not necessary. Applicants must include the following with their application: 1. Resume/CV 2. Cover
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Ph.D. in science (chemistry, physics, biology, etc.) or engineering required 7+ years of experience in computational physics or related area Proven experience coding in C/C++, Fortran, and/or Python
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preferred. Interest or expertise in single-cell and limited sample proteomics is highly desirable. Knowledge of R or Python coding would be desirable but not necessary. Applicants must include the following
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/C++, Fortran, and/or Python Proven experience with multiple parallel programming paradigms, including but not limited to; MPI, OpenMP, and CUDA (Compute Unified Device Architecture) Experience in a
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Proficiency with high-level object-oriented programming and scripting languages, such as Python, C++, Java Experience with high-performance computing environments. Understanding and experience with Python
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enrollment financial modeling and revenue forecasting in higher education settings Technical Competencies Advanced proficiency in Python, SQL, Excel, and statistical analysis software such as R Expert
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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existing and new computational methods to study multiscale processes in catalysis and photochemistry. Other projects that align with our general interest are also possible. Please see https://sdonglab.org
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forecasting. Proficiency with statistical computer languages such as Python or R. Proficiency with relational database systems (SQL) and object-based data stores. Ability to define and solve logical problems