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Field
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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of advanced photonic integrated circuits (PICs) for optical switching and processing applications. Key Responsibilities: The selected candidate will be expected to: Design, simulate, and optimize integrated
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related to staff position within a Research Infrastructure? No Offer Description Activities: The fellow will develop and optimize biocompatible micro- and nanosystems for the controlled release of
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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world
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integration, finite-volume and finite-element methods, variational formulations, structure-preserving discretisations, optimal transport, and the numerical analysis of partial differential equations. The second
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. You will design and optimize resilience mechanisms that estimate disruption risk and proactively reconfigure the transport network to enable autonomous recovery, self-healing, and graceful degradation
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-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy
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, enrollment, data collection, and data management. Optimizing the study protocol and internal procedures. Overseeing compliance and regulatory documentation. Monitoring participants throughout the remotely
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Duties Develop, apply, and analyze T-cell receptor sequencing approaches for diverse clinical cohorts. Perform and optimize molecular assays, including RT-qPCR, ddPCR, and next-generation sequencing
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Performance Optimization and Data Management. The position is based at the University of Chicago and Argonne National Laboratory, working with Dr. Katie Harrington and Prof. Jeff McMahon. The successful