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the development and validation of multi-scale fracture mechanics models. In this role, you will bridge numerical simulation with physical experiment, developing automated Python workflows, running
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, epidemiology or a closely related field . Essential Application Demonstrable programming skills in Python, including common data science / machine learning libraries (eg pandas, scikit-learn or PyTorch/JAX
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experience will be valued. Proven expertise and experience in computational statistics, machine learning, programming in R and/or Python, the development of methodological procedures, and the implementation
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skills (e.g., R, Python, MATLAB) required. The role calls for a self-driven, independent individual who can log, clean, share, assess, interpret, and write data efficiently to publish in top-tier journals
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manuscripts for international peer-reviewed journals and collaborate effectively with international research partners. Programing and data analysis skills (e.g., MATLAB, Python, R). Prior experience in in-vivo
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-scale firm-level or related datasets. Proficiency in Python and/or Stata for data management, statistical analysis, and empirical research. Experience in merging and managing large datasets from multiple
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technical reports, system documentation, and academic publications. Proficiency in job-specific technical skills, including programming and software development (e.g. Python, C++, Java, or similar languages
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phase-field simulations. Experience in developing AI or machine learning models for physics-based scientific or engineering applications. Proficiency in Python, scientific computing and machine learning
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) Experience working in Biosafety Level 2 laboratory Experience in computational data analysis, e.g., UNIX-based systems, R, Python, or similar tools for data processing and scripting Physical Requirements
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) to support the development and deployment of control systems for autonomous well construction. Expert proficiency in programming in Python or C++, and proficiency in using ANSYS. Proven ability and experience