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Centar izvrsnosti MARBLE drustvo s ogranicenom odgovornoscu za istrazivanje i razvoj | Croatia | 11 days ago
Researcher to work within the Research Department of the “CoE MARBLE – Centre of Excellence in Maritime Robotics and Technologies for Sustainable Blue Economy” (https://www.marble.eu/ ). The successful
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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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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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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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Practice and Science Department Website Link https://www.pharmacy.arizona.edu/departments-directory/pharmacy-practice-science-department Location Tucson Campus Address Tucson, AZ USA Position Highlights The
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University Abu Dhabi, seeks to recruit a motivated research or postdoctoral associate to lead the design, development, and validation of material, control systems, and algorithms for next-generation soft
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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