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solutions that support research into the vulnerabilities of AI and ML algorithms and securing against those vulnerabilities. The Secure AI Lab within the SEI’s AI Division focuses on improving the security
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conducting research into the vulnerabilities of AI and ML algorithms and securing against those vulnerabilities. The Secure AI Lab within the SEI’s AI Division focuses on improving the security and robustness
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Bioconductor. *Strong foundation in statistics, data analysis, and computational methods; familiarity with machine learning and algorithm development is desirable. *Experience working in Unix/Linux computing
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of computer vision algorithms, with a focus on assessing performance in edge deployment settings. Their role will involve supporting model development, running experiments, and analyzing results to evaluate
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mathematical subjects related to computer science, such as discrete structures, analysis of algorithms, artificial intelligence, and the theory of computation. Practical software development experience
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interdisciplinary research across AI hardware, software, and algorithms. AI Accelerators, ML Algorithms, AI Frameworks, and Model-System Codesign have been focus areas in the past - we are always excited to sponsor
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part of the diverse Caltech community. Job Summary This position involves research and evaluation of state-of-the-art algorithms for detecting and classifying safe landing zones using computer vision
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
algorithms, data models, ontologies, and semantic data harmonization and integration strategies for a variety of translational research contexts, including the following data types: clinical research variables
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | 15 days ago
learning algorithms, as well as the adaptation and optimization of existing tools. This research aligns with CBER’s efforts to enhance the development, operations, and management of FDA’s High-performance
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected