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few years, the advisors have been working on the possibilities offered by Systems, Control and Signal approaches for the development of methods for the design/understanding of systems from different
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invites applications for a PhD position focused on developing a theoretical framework for monitoring and updating adaptive learning systems (including machine learning/artificial intelligence systems) under
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and multilateral drilling concepts for cost-effective heat extraction Thermodynamic aspects of deep drilling: heat transfer, fluid–rock interaction, and downhole thermal effects on drilling performance
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also makes operations harder as services have many dependencies, failures and performance degradations can cascade across domains and slices, and platforms are often multi-vendor with different APIs and
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interaction, and downhole thermal effects on drilling performance Identifying technological and operational factors requires significantly increasing the rate of penetration (ROP) and making drilling
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, failures and performance degradations can cascade across domains and slices, and platforms are often multi-vendor with different APIs and data formats. At the same time, GenAI and Agentic AI can help
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is offered for candidates who are interested in the research and development activities in interdisciplinary areas—mechanics, materials, and artificial intelligence. Are you motivated to take a step
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activities in interdisciplinary areas—mechanics, materials, and artificial intelligence. Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with
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inference and deployment costs (e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects
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artificial intelligence (AI) sys- tems, integrating LLMs with external tools and memory components to execute complex reasoning and decision-making tasks. These agents are increasingly deployed in domains