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. 250908010) [Appointment period: each for twelve months] Duties The appointees will assist the project leader in the research project – “AiFashion: multi-modal and multi-dimensional large model based on self
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental/School research
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United Kingdom Application Deadline 21 Sep 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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solar climate intervention. Research experience with running climate model experiments on high performance computers. About UTIG UTIG (ig.utexas.edu) is one of the three research units of the Jackson
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of performance, speed, and precision. Key Responsibilities: Design and implement genAI models for embodied AI systems. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks
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these influence immune function and disease. The project combines biochemistry, molecular and cellular biology, and in vivo models to deliver a comprehensive picture of immuno-metabolic function during inflammation
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and to develop accurate cancer risk prediction models. This role involves developing computational pipelines, conducting statistical and bioinformatics analyses, and integrating multi-omics data
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the computational models using benchmarks and experimental results while assessing and improving the performance of algorithms on high-performance computing (HPC) clusters. This is a fantastic opportunity for you to
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Transport? Based in the Institute for Transport Studies at the University of Leeds, you will primarily contribute to the modelling and simulation of the integrated optimisation of Vehicle-to-Grid (V2G) energy