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- Delft University of Technology (TU Delft); 16 Oct ’25 published
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of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no ), a center for
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) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no
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university English language requirements. • Not have previously completed a PhD. • Be able to commence the Program in the year of the offer. • Enrol as a full-time PhD student. • Be prepared to be located
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the Universities of Vienna and Innsbruck as well as the IST Austria. Two PhD students will be working on cosmological inference using simulations with Oliver Hahn, and one PhD student will be working with Sylvia
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the computing industry Studentship and eligibility This EPSRC-BT co-funded Industrial CASE doctoral studentship starting in the academic year 2025/26 covers: Full time PhD tuition fees for a student with a Home
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24 Nov 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Aerospace engineering Engineering » Computer engineering Researcher Profile
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controlled and repeatable evaluation of hallucinations under diverse driving conditions. The PhD student will work closely with POST Telecom's company (Luxembourg), who is co-funding this PhD position
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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for two PhD students to join the group and research in the field of Quantum Internet. The research will target: Advanced quantum communication technologies, participating in regional, national and EU
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). The Computer Science group is looking for students to work on one of the following projects Distributed Intelligence for Self-Organising Cloud–Edge Infrastructures Carbon-Conscious Resource Scheduling for AI Workloads