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, and eye tracker data. Work Plan: - Multimodal feature extraction from EEG, HRV, gaze dynamics, and pupil size data; - Signal fusion and model training using interpretable machine learning models (e.g
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. This scholarship aims to support PhD-level studies on FAE by exploiting a new methodology that combines deep learning technology and knowledge graphs. The goal is to research and develop a new Decision Support
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from academic degree recognition processes. Preferential factors: a. Knowledge of developing artificial intelligence/machine learning (AI/ML) models and classifiers suited for embedded systems
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. Project Title: Machine learning techniques for crosstalk mitigation and new passive optical network architecturesHost institution: Iscte-IUL, PortugalThe LUMIRing project aims to deploy a MCF test bed
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6. of this Notice. Preferred factors: Knowledge in machine learning and programming (Python), deep learning (e.g., tensorflow, pytorch) and time-series modeling in marine ecology applications
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Area: Computer Science 2. Admission Requirements: Graduates (Licenciatura) in computer engineering or related area, with experience in Machine Learning/Deep Learning methods/techniques. 3. Project
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possible renewals, an accumulated period of 3 (three) years in this type of scholarship, consecutive or interpolated. Proven knowledge in: Data Science (Python) Machine Learning (Python) Remote Sensing
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with e-CALLISTO instruments or Software-Defined Radios (SDRs). · Familiarity with machine learning for astrophysical data analysis. · Knowledge of solar radio data pipelines and event classification
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experience in Data Science/Machine Learning projects or initiatives (professional projects, coursework, internships, personal projects or hackathons, etc.) Knowledge and experience with the use of tools
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | 2 months ago
: Electrotechnical and Computer Engineering. Admission requirements: Students enrolled in a PhD. program in Electrotechnical and Computer Engineering, or in related areas, or alternatively, an MSc degree in