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Field
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are the following: Obtain and maintain regulatory approval. Set up screening algorithms to identify eligible participants. Recruit participants, collect/ process samples. Design data collection tools (e.g., redcap
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machine learning, human-AI collaboration and algorithmic decision-making, recommender systems and personalization, causal inference and experimentation, digital platforms and online communities, data
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signals obtained from healthy participants and patients. Where to apply Website https://sede.unizar.es/?app=touz&opcion=mostrar&id=76878 Requirements Research FieldEngineering » Biomedical
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. The QML-CVC team (https://qml.cvc.uab.es/ ) is part of the Computer Vision Center at the Universitat Autònoma de Barcelona; the CVC is a center with over 150 persons working machine learning and computer
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
this context, the offer is about continual audiovisual robot perception, and aims to develop methods and algorithms to continuously extract cues about human behaviour from audio and visual data in real-world
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be used for the personalization of diagnosis. Where to apply Website https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079 Requirements Additional Information Eligibility criteria
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The project consists in the development algorithms for the indirect estimation
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includes the development of a preliminary processing chain featuring phase synchronization, accurate trajectory estimation, time-domain multistatic focusing, and algorithms for the estimation and
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. The research will focus on: i) the theoretical formulation of multi-view constraints for quadrics and conics; ii) the development of robust algorithms for pose estimation, reconstruction and self-calibration
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into different stages of optimization, both as priors and as feedback after optimization outcomes. Information This PhD project is a part of the CoRDS project – Confident Data-Driven Decision Support (https