464 algorithm-development-"Multiple"-"Prof"-"Prof"-"Washington-University-in-St" positions
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Field
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challenges: Successful candidates will contribute to one or more of the following research domains: development of autonomous navigation and path planning algorithms for lunar terrain traversal and regolith
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related field(s) 3. Three years of demonstrated, successful experience in algorithms development 4. Successful experience with modern C++ 5. Due to the requirements of our research contracts with the U.S
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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, developing, and implementing AI systems and data pipelines that enhance and automate university operations across multiple departments. This role is crucial in transforming manual processes into AI-driven
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teamwork above all else. This position will be working in the exciting and dynamic fields of deep learning and medical imaging. The main focus will be to develop novel deep learning algorithms to analyze
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demonstrated ability to apply these techniques in the biomedical or health informatics domain. Strong algorithm development and programming skills are required, along with excellent teamwork and communication
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plays a key role in shaping the digital presence of the Mawji Centre and supporting the JR Shaw School of Business by developing and executing social media strategies that engage students, showcase
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at advancing foundational research and application development for autonomous systems. These activities are advancing solutions of autonomous systems, intelligent machines, and human-in-the-loop control
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning