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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly skilled workforce. Research: We develop and
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, Czech Republic. Although the knowledge of Czech language is not a requirement, we do appreciate the intent to integrate into Czech academia. Your profile PhD in regional studies of Asia or the Middle East
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Posting Summary Logo Posting Number RTF00059PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
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Posting Summary Logo Posting Number RTF00059PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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measurement technique development, atmospheric modelling, and advanced methods for integrating observational and model data through data assimilation and machine learning. About the research project The overall
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). The work will involve the analysis of archival biological material from past experiments and ongoing observational studies. Where to apply Website http://www.ucc.ie/en/ Requirements Research
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co-operation with other universities/institutes and/or industry. Presently, our group consists of 1 Professor, 1 permanent researcher, 5 Postdocs and 8 PhD students. About the research project You will
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on the basis of the regulations on the recognition of academic degrees obtained abroad (learn more about the procedure for the recognition of academic degrees: https://nawa.gov.pl/en/recognition/recognition