98 parallel-processing "LCC CNRS" PhD positions at Delft University of Technology (TU Delft)
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reuse are currently made across different European contexts. You will map and analyse existing decision-making processes and strategies using qualitative research methods. Based on your findings, you will
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join a unique project which aims to develop the next generation of green and low-carbon hydrogen technologies. You will be embeded in the Process & Energy department of the Mechanical Engineering Faculty
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18 Jul 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Chemical engineering Engineering » Process engineering Researcher Profile
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? The NWA-ORC funded consortium project ABEL addresses this challenge by combining technology development with process modelling and assessment across the waste value chain. The members of the consortium
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at TU Delft, supervised by Prof. Kofi Makinwa and Dr. Padmakumar R. Rao. You will collaborate closely with the parallel metaoptics PhD researcher, SRON and the other INTERPRETER partners. Job
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implemented to collect additional data for incorporation into the Health Passport. Advanced data analysis techniques, including synchronisation, correlation analysis, feature extraction, and signal processing
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data analysis techniques, including synchronisation, correlation analysis, feature extraction, and signal processing, will be employed to identify indicators of track and bridge condition. In parallel
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Italy, exchanging insights and questions with their team developing parallel surveys for firms. Agent-Based Modeling (ABM) & Ex-Ante Assessment: Translate the empirical evidence from your surveys
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to operate in a scalable and decentralized manner while achieving obstacle avoidance using onboard sensing and adapting to changes in dynamic environments. In parallel to the theoretical and algorithmic
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biogeochemical processes that govern their behaviour. Job description The PhD candidate will develop and analyse new process-based mathematical models to improve our understanding and predictive capability