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lung tumors. We utilize a multifaceted approach that encompasses preclinical studies in immunocompetent syngeneic and genetically engineered co-mutational models of KRAS-mutant NSCLC as well as PDX/CDXs
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into a research team with established expertise in software security, program analysis, and AI-driven code intelligence, with a track record of collaboration with leading technology companies and
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learning and deep learning models for renewable energy forecasting, particularly wind power generation. Working with data-driven weather prediction models and high-resolution meteorological datasets
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innovative approaches in bit technology, hydraulic hammer systems, drilling fluids, and thermal management. The project will combine experimental insights, physical modeling, digital‑twin technologies, and AI
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, enterprise data modeling, or data engineering. Proven experience modernizing legacy data environments and designing cloud-native, AI-ready data architectures. Experience working with large, complex enterprise
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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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17 Mar 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Modelling tools Geosciences » Geology Geosciences » Hydrology Researcher
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systems that combine vision-language-action (VLA) modeling, robotic perception and interaction, and autonomous task execution. The Research Engineer will assist in system design, software implementation
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applications. The project integrates: Computational Fluid Dynamics (CFD) and multiphase flow modeling Radiative heat transfer Machine learning and reduced-order modeling Data-driven optimization for industrial
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technology Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 6 Apr 2026 - 15:00 (Europe/Amsterdam) Country Netherlands Type