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of reinforcement learning and popular modern reinforcement learning algorithms. Students will develop familiarity with both model-based and model-free reinforcement learning algorithms, including Q-learning, Actor
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position within a Research Infrastructure? No Offer Description This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is
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and develop complex, custom Artificial Intelligence models and applications. This role incorporates Machine Learning, Deep Learning, Computer Vision, Large Language Models, and Agentic AI technologies
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structures. Generative Design & Latent Space Optimisation: Leveraging generative models and agentic architectures to automate the discovery of high-performance structural configurations of medical devices
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classes and their roles in scientific applications, such as deep neural networks (DNNs), convolutional neural networks (CNNs), transformer models, and graph-based neural networks. Familiarity with software
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duties include data collection, data analysis, agent based modelling of social epistemic networks, and the writing of research articles that form part of the fellowship program. The teaching duties involve
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About the Opportunity The successful candidate will contribute to an ambitious project developing perceptual AI agents that assist humans in daily activities through behavioral understanding and
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Nurse Directors and maintains communication with the Center for Clinical and Professional Development on student performance. Evidence-based Practice Maintains expertise in the ADNP practice model
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discovery, or scientific knowledge extraction. Experience building or studying autonomous or semi-autonomous coding agents. Experience designing or implementing automated experimentation or simulation-based
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modeling builds on agent-based modeling but focuses on relations, not agents, and emphasizes the role of the researchers and their tools in constituting the model and the generated knowledge (Schlüter et al