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, including classification, regression, clustering, and deep learning algorithms. • Statistical Software: Proficiency in statistical software such as SAS, Stata, R or Python, including relevant packages
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the JAX Python library, including efficient implementations of classical numerical algorithms. 2. Extend the hybrid FEA-ML framework to include nonlinear cohesive zone models with simple traction separation
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the position description. Preferences The ideal candidate will have experience with wearable sensors and/or remote monitoring approaches and strong programming (e.g., R, Python, or similar) and writing skills
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teams of people; Strong project management experience coordinating communications and associated logistics on a multi-site research project; Advanced knowledge of Excel, Python, R, NVivo, Dedoose
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stakeholders to translate business requirements to technical specifications and coded data pipelines. Work with tools, languages, data processing frameworks, and databases such as R, Python, SQL, MongoDB, Redis
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applying target trial emulation frameworks using observational data. Experience using Python for statistical programming and data science applications. Experience using AI-assisted tools (e.g., ChatGPT
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applying target trial emulation frameworks using observational data. Experience using Python for statistical programming and data science applications. Experience using AI-assisted tools (e.g., ChatGPT
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in the creation and/or compilation of materials for academic work and educational requirements: national presentations, research manuscripts, CME reporting, etc. Act as CME Coordinator for GI Fellows
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data environment: Data Transformation & Engineering Data Preparation & Blending: Utilize technical skills, including Python and tools like Google Colab, to execute data transformation, blending, and
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., MEL, Python), procedural content generation (PGC), virtual production, lighting, and/or VFX. Candidates with expertise in other related areas of technical art are also welcome to apply. Successful