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transport planning and software engineering for policy makers and communities. As a PhD fellow, you will: Lead the development of advanced spatial analytics tools and toolkits combining GIS, Python, R, GeoAI
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recorded in humans who have seen a vast number of images from the CoCo-database (https://cocodataset.org ); and apply and interpret the architecture to local field potential data recorded in humans who have
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Demonstrated programming skills in python Experience with machine learning / deep learning (e.g., deep neural networks) Ability to take responsibility and work independently within an interdisciplinary
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characterization is a plus Experience with biomedical applications is positively evaluated Experience with data analysis using, e.g., Origin or MatLab Programming skills, e.g. proficient with Labview or Python
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have until 30.06.2026 to complete the final exam. Desired / Beneficial qualifications: Valid driver’s license. Programming and numerical analysis skills (e.g., Python, MATLAB) and/or experience with
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document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme: https://www.ntnu.edu/iv/doctoral-programme Strong background
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plague outbreaks in Eurasia between 1300 and 1900 CE. A short description of the project can be found here: https://www.synergy-plague.org/research/introduction/. The project is funded through the European
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absorption or Raman Good programming skills (preferably Python) Strong written and oral communication skills In the assessment, the emphasis is on the applicant's potential to complete a research education
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system. A strong background in statistics (a minimum of 60 ECTS in statistics). Knowledge in programming skills (e.g., R, Python). Candidates without a master’s degree have until June 30, 2026 to complete
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grade background, you may be considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme: https