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Role Description This role will give you the opportunity to help research the safe and responsible deployment of AI Foundation Models in critical applications such as healthcare and transport. You
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Fellow to conduct cutting-edge research in AI-enabled modelling and design of microwave and RF devices. The successful candidate will develop advanced physics-assisted modelling techniques to accelerate
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statistical modelling, to contribute to an ARC-funded Discovery Project investigating the psychology of how people manage competing demands inside and outside of work. The project develops and tests a novel
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characterization and theoretical modeling. Key Responsibilities: - Develop DLW fabrication workflows for hybrid photonic structures. - Integrate plasmonic nanoparticles and quantum emitters; characterize optical and
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PhD Positions Application Deadline 24 May 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Hours Per Week 37,5 Is the job funded through the EU Research
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development, model training, test rig set-up, and experimental validation. Job Requirements: The candidate must at least have a PhD Degree in AI, Robotics, Automation, Mechanical Engineering, Control
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Master’s or PhD degree in relevant areas will be advantageous. Familiarity with the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model
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-level model stability, including mixed-precision training (BF16/FP8) and gradient accumulation. Preferred Qualifications At least two years of experience beyond the PhD in a research or engineering
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culture or animal model systems. Additional Qualifications Special Instructions Required documents: Curriculum Vitae Statement of Research for PhD work Cover Letter describing your interest in the lab and
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implementation of a coupled Computational Fluid Dynamics (CFD) and fire dynamics model within the OpenFOAM framework. This model will simulate battery thermal runaway and subsequent fire propagation. The