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, or similar languages Background in machine learning or deep learning methods Knowledge of genomics, transcriptomics, evolutionary biology, and plant biology is an advantage Familiarity with large biological
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humanities and computational methods. The Fellow will pursue an independent programme of research while participating fully in the intellectual life of the three host centres. Research Themes Projects should
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seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake
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methods, work with real messy multi-source data, and contribute to infrastructure supporting population-level research and health equity. The postdoctoral fellow will be based in the Department
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, at Eberhard Karls Universität Tübingen (EKUT) to apply the developed methods to new datasets, and with our industrial partner Siemens Healthineers AG (SMS) to implement and evaluate methods that exploit prompt
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conducting high-quality research presented at international venues, and has broad scientific expertise including empirical software engineering, model- based software engineering, and formal methods
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development of novel approaches for clinical natural language processing specifically looking at the use of language models for coding clinical texts, and with a particular focus on explainability methods to be
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leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/ . Applications are now invited for
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0.5 FTE. Background Applications are invited for an ambitious Mixed Methods Research Fellow to work at the University of Birmingham across a nationally-leading research programme funded by the National
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organizational psychology and/or management and relevant research methods (particularly quantitative methods). During the doctoral project, we expect you to: Complete the doctoral programme up to completion