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application. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy
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project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
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in infectious disease epidemiology/ evolutionary biology and bioinformatics, with the ambition to advance global public health. In the first year, the successful candidate will incorporate models
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Responsibilities Develop suitable algorithmic methods for live and real-time analysis of synchronous and asynchronous data. Write research reports and publications. Analyse and interpret the results of own research
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aim to uncover the evolutionary processes contributing to the emergence and transmission of VOCs. Gaining insight into these mechanisms is crucial for informing the development of both improved and
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse
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About the Role We are looking for a Postdoctoral Research Assistant to work with Dr Chema Martin on a Human Frontiers Science Program Research Grant project entitled “Evolutionary Biophysics
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, this is achieved through two principal chemosensory systems: the main olfactory epithelium (MOE) and the vomeronasal organ (VNO) in the nose. These evolutionary conserved olfactory organs contain millions