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new models of examining the data To provide teaching to junior staff in the lab in neuroscience-related research methods, especially in pre-processing and processing of EEG data from infants/children
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integrative methods that combine health records, molecular phenotypes, and genetic data to explore disease aetiology. This position is part of the Pioneer Centre for SMARTbiomed, a national research initiative
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tasks: We are looking for a researcher who is interested in combining computational methods with literary analysis, and who enjoys working collaboratively. Stage 1 of the AI Stories project is already
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combining computational methods with literary analysis, and who enjoys working collaboratively. Stage 1 of the AI Stories project is already underway and involves developing the theoretical framework to apply
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to the research project itself. The remaining six months will be allocated to formal training. As a PhD candidate, you must participate in the Faculty of Humanities’ educational programme . The PhD programme
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environmental and social impacts; 2) enhance the integrity and efficiency of the FPL’s research efforts through the development, evaluation, and application of modern statistical methods; and 3) provide life
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will be allocated to formal training. As a PhD candidate, you must participate in the Faculty of Humanities’ educational programme . The PhD programme comprises a training component corresponding to 30
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interpersonal and communication skills. While not a must, a strong background in computational methods and/or statistical methods is a plus. Special Instructions Applicants should submit a formal application and
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fellows and other researchers. Strong interpersonal and written and verbal communication skills and ability to effectively train users and staff on proper procedures and methods for using advanced
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, 2029, if renewed. Purpose The Kowalski Lab at the University of Texas at Austin invites applications for a Postdoctoral Fellow position focused on developing advanced, AI-enabled methods for clinical