1,552 programming-"Multiple"-"U"-"Embry-Riddle-Aeronautical-University"-"Prof"-"U.S" PhD positions
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of research include integrating AI-enhanced weather forecasts with crop models, exploring tools to guide land allocation and nitrogen management, or developing dashboards that fuse multiple data streams
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Carl von Ossietzky University of Oldenburg • | Oldenburg Oldenburg, Niedersachsen | Germany | 1 day ago
provided. Participants write their theses in English. Mode of study Less than 50% online Programme duration 6 semesters Beginning Winter and summer semester Application deadline Applications are possible
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particular in relation to linear algebra Strong programming experience Ability to effectively communicate in written and spoken English Ability to work autonomously and in close interaction within a team Most
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outstanding students from all over the world to apply for PhD positions in our renowned PhD program. Based in Hamburg, our program offers excellent training and top-level structured supervision in climate
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actively contribute to this strategic initiative by researching and developing scalable, practical frameworks for implementing Trustworthy AI principles in diverse projects and across multiple technology
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an integrative approach that combines advanced multiomics, spatial transcriptomics, and structural biology with physiological assessments. By selectively perturbing key gene expression programs during homeostasis
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in the language agreed upon with his or her supervisor. Full-time / part-time full-time Programme duration 6 semesters Beginning Winter semester Application deadline The deadline for applications is 1
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Degree Dr Course location Darmstadt Teaching language English Languages The programme is in English only. Participants have to write their doctoral theses in English. Full-time / part-time full-time
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at addressing a new class of outstanding PhD researchers from all over the world. Successful candidates will receive multiple doctoral diplomas. Course organisation The EDLE programme is carried out with
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. Development of multimodal AI models that fuse data from multiple types of sensors to accurately model and predict wind turbine blade damage. Establish and develop data science pipelines for wind turbine blade