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in algorithm development using Python and ML frameworks such as PyTorch or TensorFlow. Key Competencies Work independently, as well as within a team, to ensure proper operation and maintenance
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evaluation methodologies. Experience deploying machine learning models to edge devices or mobile platforms. Strong programming skills in Python and experience with machine learning development environments
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) Proficiency with SQL and its variants (e.g., PL/SQL, T-SQL, etc.) Proficiency in programming/scripting languages (e.g., Python, Java, PowerShell, etc.) Proficiency in data engineering technologies and tools
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, or interaction for robotic systems Deep learning or applied machine learning for robotics Practical experience with robotic hardware, software development (e.g., Python, ROS, PyTorch, TensorFlow), and AI-based
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develop tools for ingesting, transforming, and integrating large, heterogeneous microscopy image datasets—including writing production-quality Python code to parse, validate, and transform microscopy data
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methods for building and validating communication and/or information theory. Candidates must have experience with computational techniques using R or Python and the ability to teach courses in computational
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for QMSS (including which course(s), if applicable) and the skills (e.g., analytical tools such as Excel, R, Tableau, Python, etc.) and experiences (e.g., jobs, internships, research, coursework, teaching
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, including branching strategies, pull requests, and documentation-as-code. Ensure all analytical scripts (SQL, R, Python) are versioned, audited, and recoverable. Implement CI/CD (Continuous Integration
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Python and/or R. Experience with workflow managers (Nextflow/Snakemake), HPC environments (SLURM, LSF), and containerization (Docker, Singularity/Apptainer) is a plus. Working knowledge of AI/ML models and
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language such as Python or Node.js) would be a plus. The candidate must be able to implement production-ready solutions in adherence to strict timelines, ensuring that deadlines are met, and that