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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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. 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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-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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graduate students, etc. In particular, the MLE hired for this position will work with Ayan Paul and Hyunju Kim at EAI and is expected to develop AI algorithms for drug synergies with a combination of public
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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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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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, 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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–machine interfaces in general. The candidate tasks will be: Develop methods and algorithms aimed at increasing the realism of virtual agents in simulation, particularly pedestrians; explore realism through
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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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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