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Field
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? No Offer Description We have two exciting PhD positions at the intersection of formal software verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based
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impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. Challenge. Change. Impact! Faculty Architecture & the Built Environment The Faculty
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analyses Develop user-facing data products (e.g., risk maps, warning systems) and contribute to software architecture (APIs, microservices, web apps) Publish and present your research, contribute to open
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expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and
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iii) developing socially just heat adaptation strategies, that are context and conflict sensitive. This PhD position is situated at the Faculty of Architecture and the Built Environment, Department
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an understanding of complex systems with a vast amount of software requires effective architecture explanation frameworks, visualizations and identification of architectural refactoring opportunities in legacy
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highly motivated Ph.D. candidate. The background is preferably in electrical engineering, computer architecture, control, computational neuroscience, or similar fields. Unconventional backgrounds supported
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, dynamic simulation, additive/classical fabrication; sensorization, actuation, and integration on gantry/field robots. For PhD#3 (DT): Design software architecture; integrate multi-modal data and models (e.g
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domains. Develop hybrid AI architectures combining symbolic domain knowledge, real-time data streams, and probabilistic inference. Design and evaluate decision support tools capable of interacting with
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Engineering). - Theoretical foundations of 6G RAN and autonomous systems o Proven knowledge of AI-native RAN systems. Indicative skills/experience: - Deep understanding of 5G/6G RAN architecture (O-RAN, NG-RAN