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a strong background in computational modeling, optimization, and systems engineering, eager to develop advanced design and simulation frameworks for battery pack topology and e-powertrain integration
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Do you have passion for sustainable design and development of new materials by combining experiments and modeling? We are looking for motivated candidates for three PhD positions in AI-STEEL Project
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
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the Industrial Engineering and Management Sciences (IEMS) section in the High-tech Business & Entrepreneurship (HBE) department of the University of Twente. This PhD position, designed with Thales NL, as an
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public data sources such as Certificate Transparency (CT) logs, the Ph.D. candidate will design and implement techniques to flag suspicious registrations in near real-time, helping shift the response model
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: Develop real-time optimization and hybrid AI models for end-to-end multimodal transport planning under uncertainty. Design synchronization, consolidation, and matchmaking algorithms that align prefab
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two global industry leaders, Apollo Tyres and LANXESS. The project is dedicated to designing and implementing smart, protective delivery systems for critical additives. The aim is to shield these agents
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antibodies, MIPs have molecule-specific binding sites formed during synthesis, enabling selective detection of antibiotics and other biomarkers. Building on the department’s pioneering work, you will design
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will