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Department of Health Technology and Informatics Postdoctoral Fellow / Part-time Research Associate (Ref. 251014023) (1) Postdoctoral Fellow [Appointment period: twelve months] (2) Part-time Research
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) and reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing
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United Kingdom Application Deadline 30 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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the Sterne-Weiler Lab i n Computational Biology / Discovery Oncology. The postdoctoral position is focused on developing and applying foundational AI models to investigate clinically relevant cancer
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to uncover protocol/waveform features, impairments due to implementations and urban environment that could facilitate/impair UE localization. Develop the signal model for localization of UEs in the urban
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will join a dynamic, interdisciplinary team exploring the frontiers of mass spectrometry imaging and molecular modelling. As our Research Fellow, you will lead the computational arm of a Leverhulme Trust
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the development of new anchoring technologies for floating offshore wind turbines. Your role will focus primarily on the development of simplified computational models, and you will contribute
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8 Oct 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Biomedical engineering Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
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models of program adoption and diffusion. Contribute to the broader research agenda by undertaking additional scholarly inquiry and program evaluation as required to advance innovation, policy relevance
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | about 1 month ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and