653 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation"-"U.S" Fellowship positions in United Kingdom
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with epilepsy across multiple NHS hospitals. They are expected to have some experience working with NLP in general and LLMs in particular. They will also help to further develop machine learning models
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future development of an ongoing epilepsy research project funded by the UK Epilepsy Research Institute. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on
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for researchers requesting advice on the design of their research and will be responsible for supporting the researcher to design their research study. There will be the opportunity to develop and apply your
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an STFC-funded postdoctoral researcher to develop new inverse modelling (‘retrieval’) methods to extract 3D information from JWST secondary eclipse observations. The models will be applied to JWST
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, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning
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-learningdisability/ ) a team of researchers showed that adults with Profound and Multiple Learning Disabilities (PMLD) and their family carers were disproportionately impacted by the COVID-19 pandemic. The post holder
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and deploy the most promising prototypes at multiple field sites around the world via our global collaborator network. An important part of the work will be publishing high quality research papers in
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including malaria, have experience and understanding in using multiple metrics for analysis, experience with design and implementation of study protocols, experience of data analysis in Stata and programming
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and deploy the most promising prototypes at multiple field sites around the world via our global collaborator network. An important part of the work will be publishing high quality research papers in
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for aircraft systems. You will integrate heterogeneous data streams (from multiple sources, such as sensory, physics model, etc.), flag impending failures, pinpoint and trace back the origin of system faults