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modeling of polymeric, reinforced, and porous materials, with strong expertise in large deformations and numerical homogenization. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7649-JULDIA
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, Computer Science, Engineering and Genomics. Previous experience working with disease vector data is not essential and we encourage all applicants interested in large-scale data management, computational design and
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, harmonization, aggregation and analysis of clinical data for a large ophthalmology repository. Extract information from unstructured electronic health record text using large language models (LLMs) and clinical
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experience in the processing and integration of massive datasets (‘big data’), they will contribute to ecological modelling, environmental impact forecasting, and soil biodiversity analysis in the central
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major hurdles in the use of genomic data in public health – access to big data sets, the technology to analyse these data, and the knowledge to interpret the results. In this role, you will develop
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Frameworks. Information on the cutting-edge, multidisciplinary research and teaching at the Institute for DSAI can be found at https://dsai.bogazici.edu.tr/ . By leveraging the big data, Boğaziçi DSAI’s
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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» Psychoanalytic studiesYears of Research Experience4 - 10 Additional Information Eligibility criteria PhD in Educational Sciences or Psychology Other specific requirements: -experience in large-scale IEA Assessment
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post-operative animal care including documentation; 2) assisting with all large animal procedures, 3) record keeping, data acquisition, and sample collection and processing during large animal surgery; 4
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. Please check our website (www.ec2-big-nse.de ). Submit application to https://www.ec2-big-nse.de Accommodation The BIG-NSE administration office supports students in their search for suitable accommodation