Sebastien Gros
4 weeks ago
PhD fellowship in statistical models and methods for large-scale spatio-temporal data Norwegian University of Science and Technology in Norway
Degree Level
PhD
Field of study
not provided
Funding
Full funding availableCountry
Norway
University
Norwegian University of Science and Technology

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About this position
New PhD fellowship at the Norwegian University of Science and Technology (NTNU) in the area of statistical models and methods for large-scale spatio-temporal data. The position is announced in connection with the Norwegian Center on AI for Decisions and is described as part of an exciting research project with a strong industrial and academic ecosystem.
This opportunity is relevant for candidates interested in statistics, mathematical modeling, computer science, and data-driven methods for complex spatio-temporal data. The post highlights strong supervision and a research environment spanning academia and industry.
Institution: Norwegian University of Science and Technology (NTNU), Norway.
Position level: PhD opening.
Research keywords: statistical models, methods, large-scale data, spatio-temporal analysis, AI for decisions.
Funding: PhD fellowship; no stipend amount or detailed funding package is stated in the post excerpt.
Eligibility: The excerpt does not list detailed requirements such as degree background, grades, or language tests; applicants should consult the full Jobbnorge advertisement for complete criteria.
Application: Use the Jobbnorge link provided in the post to access the official vacancy page and submit the application through the portal. Check the full announcement for documents, deadline, and any additional instructions.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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