220 structures "https:" "https:" "https:" "https:" "NOVA.id" PhD scholarships in Netherlands
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- University of Amsterdam (UvA); Published yesterday
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. Guidelines for applicants: https://phdpositionswetsus.eu/guide-for-applicants/ Where to apply Website https://phdpositionswetsus.eu/ Requirements Research FieldAgricultural sciences » Soil scienceEducation
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to enable this through inclusive policies and innovative projects led by teams of staff and students. We encourage you to apply for this position. Where to apply Website https://www.academictransfer.com/en
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investigate how glycan structures affect immune responses in peritoneal metastasis and whether glycan inhibition can restore anti-tumor immunity. You will: investigate how tumor-associated glycan structures
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bottlenecks in clinical radiology workflows through observations, structured workflow mapping, and close collaboration with clinical staff. Design, develop, and evaluate AI-based and automated workflow
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about 5%. Where to apply Website https://www.academictransfer.com/en/jobs/358945/phd-position-factual-belief-pol… Requirements Specific Requirements Required: You hold (or expect to obtain before starting
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collaboration with industrial and governmental stakeholders, addressing societal concerns related to land subsidence, uplift, and structural safety in the Grijpskerk, Norg, and Schoonebeek regions. The goal
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. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate . Where to apply Website https://www.academictransfer.com/en/jobs
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actively contribute to meetings and gatherings of the Social Context of Aging group at the VU (https://vu.nl/nl/over-de-vu/meer-over/the-social-context-of-aging-soca ) ,the LASA research team in
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to apply Website https://www.academictransfer.com/en/jobs/358013/phd-mainstreaming-nature-based-… Requirements Specific Requirements Knowledge, Skills & Experience (Essential): A Master in Urban Planning
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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing