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methods that aim to transform scientific discovery and leverage high-performance computing. Specifically, this will include research in : 1. Developing large-scale agent-based and other complex systems
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thesis has been approved, along with a documented indication of the expected date of formal graduation. It is the responsibility of the faculty mentor to verify this documentation. The documentation must
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computer programming in R and Python *Formal training or experience applying quantitative and spatial methods to human-environment questions *Excellent academic writing and communication skills in English
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and
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. Areas of application include lithium-ion batteries, high-salinity water treatment, and separations. The researcher will employ molecular dynamics (MD) and quantum mechanical (QM) methods to develop and
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of information processing), and formal epistemology (in particular, formal representations of inattentiveness and unawareness). This project will involve philosophical / linguistic analysis, experiments with human
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to develop innovative methods and actionable tools for detecting, analyzing, and preventing vulnerabilities in supply chain systems, leveraging state-of-the-art AI and ML techniques to improve overall security
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and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al., 2019; Pedersini et al., 2023). We combine
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design