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of approximately 1.7 million square feet and high-performance computing facilities at the DOD Supercomputing Research Center. This opportunity has multiple projects based out of the ERDC Field Research Facility in
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous PhD project. In addition to electromagnetic geophysics
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electromagnetic data during drilling. This includes the further development and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous
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dialogue on AI governance. Manage multiple projects simultaneously, ensuring timelines are met and resources are effectively allocated. Collaboration & Knowledge Exchange Collaborate with policymakers
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particular sequential, multiple assignment, and randomized trial design. You will have the opportunity to mentor the PhD students on the team. Experience in any of the following areas may be useful: SMART