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instrumentation and clinical data. The position combines machine learning, statistical data analysis, scientific programming, and research software maintenance within biomedical and metabolomics-oriented projects
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spatiotemporal patterns of gene expression associated with these diseases through the development and application of machine learning methods for data analysis and integration. The thesis will be carried out in
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University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC) | Spain | 2 months ago
(CompBioCat) research group at the Institute of Computational Chemistry and Catalysis (IQCC, http://iqcc.udg.edu ), University of Girona (Spain), is seeking a highly motivated PhD candidate to join the ERC
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processes. • Apply machine learning techniques and advanced statistical analysis to extract knowledge from complex datasets. • Participate in the evaluation and optimisation of high-performance scientific
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. -Estimation of environmental indicators related to biodiversity and ecological connectivity. -Design, development, and benchmarking of machine learning models for indicator estimation. -Design, development, and
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. Experience with finite element software development. Experience with machine learning and data-driven modelling. Experience with high-performance computing. Previous scientific publications. Qualification
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Institut d’Investigació Biomèdica de Girona Dr. Josep Trueta (IDIBGI-CERCA) | Spain | about 2 months ago
practical knowledge of statistical and programming packages is mandatory, including R, Python, and/or SQL. Extensive experience with advanced statistical techniques and algorithms, such as Machine Learning
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e intercepción y análisis de comunicaciones. -Advanced knowledge of machine learning in artificial intelligence. -Strong proficiency in programming languages, particularly Python. -Advanced knowledge
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alternative phonological descriptions into the extended BML used by Animics also play an important role. Advances in this regard could help generate resources to progress toward a medium-term goal: the machine
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to research projects involving big data analytics, artificial intelligence, and machine learning applied to stroke care. Support the development and validation of predictive models and clinical decision-support