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include MATLAB, Labview, Python and/or C++. Requirements: PhD Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability
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engineering pipelines. Implement models in Python using frameworks such as PyTorch, TensorFlow. Perform statistical analyses and model benchmarking against existing methods. Collaborate with wet-lab scientists
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For Someone Who • Has a PhD in computational biology, genomics, bioinformatics, microbiology, or a related field. • Is fluent in Python/R and Unix-based workflows. • Has experience with microbial genomics
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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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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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focus on quantum impurity models (particularly Kondo model). • Strong computational skills (with Python or Julia or C++ or Matlab or equivalent) and using numerical techniques such as exact
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advanced analytical skills including statistical programming in Python, Stata, R, and/or SAS • Excellent communication and presentation skills • An ability to work both independently and in teams Benefits
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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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date). Strong background in power systems analysis (OPF, state estimation) and numerical optimization/control. Proficiency with Python/MATLAB and power-system toolchains (e.g., MATPOWER/OpenDSS
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the following areas: Performing and/or analyzing functional genomics experiments Competence with Unix environment, R, Python, high performing cluster Familiarity with machine learning Have taken coursework in