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Field
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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programming and data analysis (Python, MATLAB, or equivalent). Experience with machine learning, data-driven modeling, or AI methods applied to physical sciences datasets. Familiarity with handling and
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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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-driven applications. Demonstrated expertise in designing, implementing, and evaluating complex software systems. Strong programming skills in relevant languages (e.g., Python, C++, Java) and experience
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observational health data, particularly electronic health records (EHR) Proficiency in statistical programming (e.g., R or Python) and reproducible research workflows Demonstrated ability to lead analyses and
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-driven applications. Demonstrated expertise in designing, implementing, and evaluating complex software systems. Strong programming skills in relevant languages (e.g., Python, C++, Java) and experience
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systems, social sciences, epidemiology or other health-related fields. Demonstrated proficiency through previous developed analytical codes with R Language for Statistical Computing and/or Python The ideal
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. Familiarity with programming languages such as MATLAB and Python, and the ability to work with large imaging datasets Excellent communication and presentation skills, with the ability to prepare high-quality
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Python and machine learning frameworks (e.g., PyTorch, Jax, scikit-learn) applied to genomic/related datasets. Experience with sequence modeling architectures and interpretable AI methods (SHAP, Integrated
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experience: Python, MATLAB, SPSS, Shell. Experience in working with Linux workstation. Excellent organizational and time-management skills and ability to self-direct work. Ability to work as a team member