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faculty in developing theory and application tools for artificial intelligence (AI), and training efficient data analytics. 60% - Leading research in AI will include generative models, algorithms and
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experience of application of artificial intelligence including machine learning and deep learning algorithms. Documented programming skills in Python, R, or MATLAB. Very good knowledge of English, spoken and
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to apply. Responsibilities include: Algorithm development and/or software design Develop C/C++ or equivalent code to interface with developed hardware and associated interfaces (SPI, I2C, etc) Integration
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coding using R and adeptness in using RStudio for data analysis. Produce comprehensive reports and presentations in PDF and HTML formats using R Markdown. Knowledge of machine learning algorithms
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, including image acquisition, processing, analysis, and interpretation Develop and validate new imaging techniques, algorithms, or software to improve diagnostic accuracy and patient outcomes Collaborate with
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, applying and validating your algorithms through laboratory experiments. A PhD in Chemistry, Biology, Computer Science, or related fields with a focus on protein engineering. Proficiency in Python programming
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to testing. Analyses, designs and builds component-based applications including introduction of an application layer, modeling techniques, component and object-oriented design, complex algorithmic
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discovery with a strong emphasis on domain-driven impact. Develop, optimize, and transition algorithm prototypes to robust implementations Work with ORNL researchers, as well as internal and external project
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reports and presentations in PDF and HTML formats using R Markdown. Knowledge of machine learning algorithms. Proficiency in Canvas and content organization. Excellent communication skills. Responsible and
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. Strong applied knowledge of classical machine learning algorithms, including implementation with scikit-learn, model evaluation using metrics such as accuracy, precision, recall, F1-score, and