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provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute
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. The Postdoctoral Fellow will hold a PhD or equivalent degree (e.g., ScD, MD, DVM, DrPH). Under the guidance of Dr. William Pan, the Postdoctoral Fellow will perform full-time, independent research, consistent with
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developing new inverse modelling (‘retrieval’) methods to extract 3D information from JWST secondary eclipse observations. The models will be applied to JWST observations of giant transiting exoplanets
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Assurance and verification offerings for AI are fragmented and target specific areas of AI lifecycle (e.g. model assurance or prompt injections) without offering a unified view of the security
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. About you You must hold (or be close to completion of) a relevant PhD/DPhil, together with relevant experience, and posses sufficient specialist knowledge in the discipline. You should be able to conduct
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publications, conference papers, and technical reports). Present research results at conferences, consortium meetings, and industrial forums. Support supervision and mentoring of PhD and MSc students. Engage in
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. This is an excellent opportunity to be part of an interdisciplinary and international research collaboration, spanning health policy, economics, medicine, and public health. Candidates should have a PhD (or
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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John Williamson, and Dr Sebastian Stein. The job requires the proven ability to develop novel theory and build and evaluate working interactive prototypes involving complex computational models