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, finger, and multimodal) under controlled and semi-wild conditions. Develop AI-based algorithms for biometric trust assessment, anti-fraud analytics, and secure onboarding. Lead the deployment and
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-modal”) neural + behavioral disease-state models. The purpose of the research project(s) this position supports: The purpose of the research supported by this position is to develop a computational
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. Kurusch Ebrahimi‑Fard and is connected to the research activities of the national project SURE‑AI. The PhD project focuses on developing mathematical and computational methods based on path signatures and
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FLEX/FFPE), ATACseq, nCounter panels, spatial transcriptomics, ChIP-seq, cut-and-run and others Apply machine learning algorithms to clinical multi-omic datasets. Assist with collaborative and service
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to integrate large and complex preference datasets with information at individual level, with specific attention to open and reproducible research, e.g., in the development of codes and algorithms. We will focus
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is on fundamental limits, and development of algorithms and methods. Applications can be found in, for example, signal, image and video processing for autonomous vehicles and swarms of drones; massive
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these interactions and their evolution are studied, with a few privileged fields that are particularly sensitive to these interactions, whether local or global. Each of these socio-ecosystems is used as a laboratory
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, towards a common goal of transforming the diagnostics and preservation of cultural heritage by developing innovative non-destructive evaluation techniques and advanced digital tools for diagnostics
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optimizing reaction conditions compared to human decision making and design of experiments techniques. We will develop a Bayesian optimization algorithm for the optimization of reaction yields
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. The mission is to address challenges facing scalable quantum computing and to develop novel and improved platforms for quantum computation and communication and thus strengthen U.S. leadership in QIST