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Field
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machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal learning, and 3D perception. An affinity for translating
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faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies
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intelligence, software engineering, geoinformatics, or a strongly quantitative geoscience discipline. Essential Experience of game development using engines such as Unity, evidenced through a portfolio of work
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on RFSoCs or software-defined radios. ▪ Conducting real-world experiments to investigate deviations between theoretical models, software simulations, channel emulations, and hardware implementations
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and Information Sciences (iCIS) at Radboud University in Nijmegen. iCIS conducts world-class research in machine learning, software science and digital security, and consistently ranks among the top
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framework for MR image super resolution using high fidelity CFD data. Validate the software using MRI scans of arterial flow phantoms. Collaborate directly with clinicians to maximise the translational and
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skills with programming software such as R, Python or Matlab. Professional working proficiency in English, including scientific writing.
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develops LLMs and agentic AI systems for scientific discovery, engineering and physical systems. We investigate how AI can reason about scientific problems, interact with simulation software and support the
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. Ability to develop, understand, and critically evaluate machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal
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of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied