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Description NOTICE OF ONE PhD Research studentship, for the project “LEARNING BOLSTER”, (2023.17516.ICDT), AT THE CENTER FOR PSYCHOLOGY OF THE UNIVERSITY OF PORTO (CPUP) IN THE FACULTY OF PSYCHOLOGY AND
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to the lack of accurate models, machine learning-based problem solving is now revolutionizing almost every field of science and technology. FuturoChrom aims at developing model-free, purely reinforcement
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, we need an imaging scheme that captures relevant features at different length scales and integrates them into a single reconstruction volume. This PhD project focuses on learning-based phase retrieval
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that learn nonlinear cross-fidelity correlations. More broadly, scientific machine learning methods such as physics-informed neural networks (PINNs) and operator learning (DeepONet, Fourier Neural Operator
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-capable and prosperous. Founded in 1898, Northeastern is a global research university and the recognized leader in experience-driven lifelong learning. Our world-renowned experiential approach empowers our
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performance, yet their atomic-scale origin and role in reactivity remain poorly understood. The project addresses this open problem by integrating high-throughput Density Functional Theory, machine-learning
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application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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environment. Key research Objectives: AI Innovation (Taxonomic Identification): Developing and optimizing deep-learning architectures (e.g., YOLO) for the automated detection and classification of nocturnal
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increasingly rely on data-driven models to extract, represent, and interpret information from complex and evolving environments. Traditional machine learning approaches, as well as many classical signal