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Field
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). The candidate should have hands-on experience developing state-of-the-art machine learning models, particularly deep neural networks (experience with graph neural networks is highly valued). Their background
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, Artificial Intelligence, Machine Learning or Cybersecurity or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in, for example, Machine Learning, Deep Learning
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still
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, visiting researcher opportunities, access to modern GPU clusters for deep learning research, and strong academic-industry connections. CADIA's commitment to open science aligns perfectly with this project's
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robust and fast HSI-based detection method using deep learning (CNNs and pixel-wise classification). • Creating a comprehensive dataset of hyperspectral images for training and testing models
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reducing demand. However, demand drivers are manifold, including technology advancements, population and economic trends, and their future developments come with deep uncertainties. Infrastructure policies
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unique atmosphere where there is expertise to dig deep into computational modelling, while remaining connected to the experimental side. This interdisciplinary atmosphere has been a main catalyst for many
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substrates while advancing our understanding of deep learning through dynamical systems theory. You will work with two cutting-edge experimental systems: (1) light-controlled active particle ensembles
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker