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machine learning within the scope of ACAG. The postdoc will have various opportunities for professional development, including contributing to and leading grant proposal development (e.g., external
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
and experimental, in the broad field of nonlinear mechanics. Preference will be given to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure
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collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer Science, or a related field. Extensive and sound knowledge of ML, AI, DNN, LLMs/VLMs, Multimodal LLMs, RAG, Agentic
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position focused on advancing crop production and physiology through field experimentation, computation (statistics and machine learning), and process-based models. The successful candidate will have an
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Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware
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across the broader TU Delft research community. Job requirements PhD in computer science, AI, machine learning, data science, network science, computational social science, or a related field. Expertise in
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analytics, including correlation analysis and machine learning techniques. Preferred Qualifications: Experience with microstructure characterization techniques (SEM, EBSD, TEM, XRD). Experience in mechanical
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, and machine learning within the scope of ACAG. The postdoc will have various opportunities for professional development, including contributing to and leading grant proposal development (e.g., external
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companies writing scientific publications in peer-reviewed journals acquiring and implementing third-party funded projects. Other responsibilities include mentoring and supervising PhD students, Bachelor’s
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to learn about, (road) network traffic flow theory and simulation. You are interested in mentoring and supporting MSc and PhD students. You are a machine learning enthusiast (and realist). You love coding