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genomics data, writing Python code for data analysis, and a downstream R pipeline for post-processing data using standard Bioinformatics libraries from Bioconductor. There will be opportunities
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Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems Foundational courses (for Connect pathway students): Python programming, Mathematical Concepts, Research Methods and Scientific Writing
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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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. 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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Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems Foundational courses (for Connect pathway students): Python programming, Mathematical Concepts, Research Methods and Scientific Writing
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personal style willing to receive assistance and coaching when needed from the faculty lead. Prior experience in a diverse higher education institution preferred. Knowledge of Python and/or R programming
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, materials science, chemical engineering, bioengineering, or a closely related field. The candidate should have strong problem-solving skills and be highly motivated. Programming skills (Python or Fortran
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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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skills with proficiency in Python, TensorFlow/PyTorch, and experience with containerized deployments and MLOps practices. Data Pipeline Engineering: Extensive experience with end-to-end data pipelines
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personal style willing to receive assistance and coaching when needed from the faculty lead. Prior experience in a diverse higher education institution preferred. Knowledge of Python and/or R programming