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Funding Source: EPSRC DTP Sponsor Company: Roxel Ltd Start Date: 1/10/2025 Project Page – Centre Project Overview The aim of this PhD is to investigate RAM formulation chemistry of polyol binders
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challenges holding back an even wider usage. This PhD position is part of the national NanoMedNL consortium that aims to counter these challenges and thereby accelerate and support the development of novel
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. The PhD candidate will investigate how AI and above all Generative AI (GenAI) can be leveraged
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 21 days ago
Kovtun) at the City Campus invites applications for the position as PhD student (f/m/d). We are looking to recruit a PhD student for projects in structural studies of membrane trafficking using cryo
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The Laboratory of Cortical Information Processing | Vision to Action at NERF (www.nerf.be ) invites applications for a PhD student to join a Simons Foundation-funded, collaborative research
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The Laboratory of Cortical Information Processing | Vision to Action at NERF ( www.nerf.be ) invites applications for a PhD student to join a Simons Foundation-funded, collaborative research
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The Department of Mathematics and Computer Science at the University of Southern Denmark (Odense) invites applications for a PhD scholarship in computer science under the umbrella of the Danish
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PhD Position Reorganisation mechanisms in nano-structured silicon carbide TU Wien is Austria's largest institution of research and higher education in the fields of technology and natural sciences
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the communicative and emotional demands of social interactions using a multidisciplinary, cognitive neuroscience approach. We are seeking two highly motivated PhD candidates to join our interdisciplinary research
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust