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education to working life. The PhD supervisor will be Senior Researcher Ingunn Ness. Please contact her for more information about the project. About the work tasks: investigate how multi-agent ecosystems
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, patient motion, and more. Today, these parameters are either manually configured, heuristically optimized, or compensated post hoc using multi-level calibration scans or corrections, which introduces
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of nano-scale plastic particles (nanoplastics; 1-1000 nm) which represent the majority of plastic in the ocean. The impact of nanoplastics on marine life and ecosystem function requires attention
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and
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the properties of composite, biological networks which consist of stiff filaments and liquid inclusions which arise from liquid-liquid phase separation. We will use a multi-scale approach bridging scales from
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optimization – with rigorous theoretical analysis. The ideal candidate has strong machine learning and AI expertise and is comfortable with – or eager to learn – large-scale multi-GPU experimentation
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liquid methods, facilitating improved battery lifespan, reliability, and safety during ultra-fast charging and high discharge cycles. However, the multi-scale thermofluid dynamics complexities of boiling
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for corneal regeneration through state-of-the-art (single-cell) multi-omics analysis. You will collaborate with other doctoral candidates in STEM-CORE through joint projects, secondments and network training
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for fine-tuning and deployment of large-scale models. What’s more, multimodal models are particularly vulnerable to data uncertainty, modality dropout, and noise propagation, which can degrade robustness and
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nanogaps at atomic scale create extreme optical hotspots that enhance light-matter interactions, making them ideal for achieving low-energy, high-speed optical switching. The research will focus