78 modelling-complexity-geocomputation Postdoctoral positions at University of Oxford
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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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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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good understanding of the relevant basic theory, skills in data analysis and numerical modelling, and a strong research track record. Please direct enquiries about the role to: Only applications received
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concept of agents has come to the fore again, prompted by the rise of Large Language Models (LLMs) – put crudely, the idea is to use LLMs, in the sense of being powerful general purpose intelligent systems
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record in studying humans and machine learning models, in the context of human social behaviour, learning, decision-making, or a related area. A proven track record of publishing work as lead author in
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(LiB’s). You will be responsible for: • Developing models and simulations of the electrode fabrication process, sensors, and actuators. • Developing a demonstrator of a soft sensing system that
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. Concurrently, you will develop lower order analytical models and perform high fidelity computational simulations to corroborate experimental findings and propose other configurations to be subsequently
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into the ethical governance of Large Language Models (LLMs), as part of the prestigious Divirsibus Vis Plurima Solvo project. The position is full-time and fixed term for 41 months or to the funding end date of 30
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of complex biological oligosaccharides and their site of attachment on fusion glycoprotein complexes isolated from viral surfaces (e.g. dengue and HIV-1). We are looking for a highly motivated researcher
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of code to conduct complex comparative genomics, implement HMM searching strategies and conduct phylogenetic analysis on a grand scale while making use of sophisticated phylogenetic methods (for example