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Requirements: Selection will prioritize candidates with interest and/or experience in the following areas: a) Basic knowledge of machine learning techniques, with interest in exploring algorithms such as
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validation of machine learning algorithms for container transport planning problems, using real-time data from the tracking system. Taking a logistics perspective, the main objective is to consider the main
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algorithms (e.g., filtering, normalization, and event detection) to characterize human–robot interaction patterns, with a particular focus on detecting movement intention and potential risk situations. iv
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Reconstruction from clinical arthroscopy video. The research will focus on investigating and advancing multi-view feed-forward algorithms to tackle the specific challenges of the arthroscopic environment, where
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algorithms for classifying modes of locomotion and assessing fall risk; iv) integration and control of balance recovery through slip detection tools in a commercial exoskeleton, using ROS2, DMPs, CPGs, and
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quantum advantage; Classical simulation algorithms for noisy quantum devices; Boson sampling and related quantum computational advantage proposals; Mandatory Qualifications Education PhD degree in Physics
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Researcher, of the FCiências.ID Scientific Research Career, within the scope of the project HOFGA: The Hardness of Finding Good Algorithms (Ref. HORIZON-ERC-STG-101041696), financed by the European Union´s
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intelligence algorithms.”, financed by National public entities (IFAP IP), under the following conditions: Scientific Area: Geospatial Engineering Admission requirements: Candidates must meet the following
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activities will be developed in the Power Electronics area, focusing on programming control algorithms on a Xilinx FPGA. This project aims to implement internal fault tolerance in a power electronics
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requirements, as well as the design of data models, synchronisation algorithms and analysis and learning models applied to brain and physiological signals. The objectives of this fellowship are: 1. To survey