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are interested in combining disciplinary knowledge with the skills of a data scientist and working at the interface of bioinformatics, medical informatics, databases, data mining, machine learning, applied
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, data science using EHRs, machine learning, data mining, and natural language processing are preferred. Job Description: Develop large language models and other methods and tools to effectively use
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conditions, and non-i.i.d. data—where robustness and credible inference are critical. Research topics Hybrid learning & physics-based AI — Integrating process-based models with ML Unstructured data mining
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 5 hours ago
-time / part-time full-time Programme duration 6 semesters Beginning Winter and summer semester Application periods This programme has no deadline listed. More information on application periods Please
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Status: Open Applications open: 1/06/2023 Applications close: 17/12/2030 View printable version [.pdf] About this scholarship Description/Applicant information This Curtin top up scholarship
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 1 day ago
-time / part-time full-time Programme duration 6 semesters Beginning Winter and summer semester Application periods This programme has no deadline listed. More information on application periods Please
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involve aspects of (geo-)microbiology, soil science, atmospheric measurement techniques, atmospheric transport models, terrestrial and atmospheric remote sensing, model data integration, data mining, land
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Status: Open Applications open: 1/07/2026 Applications accepted at any time View printable version [.pdf] About this scholarship Description/Applicant information Please note that this is FOR
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candidate. The PhD project will focus on data analytics, data mining, and statistical modelling of complex biological system in crops. The project will have access to large volume of state-of-the-art Next
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challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up