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within and beyond the University. We are looking for a Research Fellow to research on the areas of Robotics and AI using advanced modeling and simulation. Key Responsibilities: Development of a quality
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applies AI to tackle challenges in aquaculture and drug delivery, working at the interface of materials science, biology, and computational modeling. Key Responsibilities: Lead and execute AI-driven
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4 Sep 2025 Job Information Organisation/Company Instituto Pedro Nunes Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions
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within and beyond the University. We are looking for a Research Fellow to research on the areas of 3D printing technologies using advanced modeling and simulation. Key Responsibilities: Development
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schools and research centres within and beyond the University. We are looking for a Research Fellow to research on the areas of 3D printing technologies using advanced modeling and simulation. Key
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carry out and oversee research projects in multimodal, generative, and embodied AI. The role will focus on designing, developing, analyzing, and evaluating large AI models to push the current boundaries
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Postdoctoral Research Fellow for a highly interdisciplinary and collaborative project. The main objective of the project is to develop multiphysics models for urban CFD in OpenFOAM. At Computational Combustion
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research program advancing carbon-neutral energy systems modelling for Australia's energy transition. This role focuses on the development and application of advanced forecasting and scenario analysis
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 11 days ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and