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framework to train, test and validate a machine learning-based forward operator to enable the assimilation of SAR data into a crop growth model. Be responsible for the curation, storage and maintenance
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). This interdisciplinary project investigates how AI — specifically large language model (LLM)-based agents — can act as adaptive social agents to support students' collaborative learning in Challenge-Based Learning (CBL
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processing and statistical data analysis. Familiarity with flow modelling techniques (CFD) or machine learning for fluid flows. Aptitude for team work and excellent communication skills in spoken and written
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your academic career? Your interests lie in the field of machine learning techniques, particularly artificial neural networks, and deep learning? And you would like to continue your research
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measurement techniques and PIV. Familiarity with optics, lasers, image processing and statistical data analysis. Familiarity with flow modelling techniques (CFD) or machine learning for fluid flows. Aptitude
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what you bring. Do you recognize yourself in this? You have completed a PhD in data science and/or artificial intelligence. You have gained knowledge of various machine learning techniques, particularly
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or more of the following areas: (1) Generative AI and machine learning, (2) affective computing, (3) human-computer interaction or collaborative AI, and (4) interaction design, experimental design or
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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large language models (LLMs), natural language processing (NLP), and/or machine learning, with a verifiable track record (e.g., publications, thesis, or open-source contributions). Proficiency in Python
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cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization. As a