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on the ERC project and your own research interests. You will apply state-of-art methods of social network analysis, such as Stochastic Actor-Oriented Models (training will be available). You will produce high
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and assessment of ocular inflammation models, such as intravitreal injections, ocular imaging techniques and flow cytometry. Moreover, applicants will perform a variety of additional procedures such as
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connected large wind energy system dynamic modelling, control and analysis. In particular, the objective of this research programme is to lay the foundations of a new, model and methodology for Advanced wind
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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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, or computational modelling. This post is based at the Department of Computer Science and on-site working is required. Remote and part-time working options must be agreed with Professor Nobuko Yoshida. What We Offer
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level of detail extracted from these experiments. As part of this role, you will work closely with other researchers to translate these experimental results into our numerical models, helping to improve
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candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities
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social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data, it will examine how polarized content influences stress, anxiety
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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, control theory and contemporary stochastic volatility modeling. The successful candidate will cooperate with the members of Christa Cuchiero’s group as well as with the associated research groups