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. Ability to handle large volumes of data and familiarity with household surveys are required, alongside solid data analysis skills (R, Stata, Python, etc.) and familiarity with academic writing and
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include: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory
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, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C++) and GUI development
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data analysis skills (R, Stata, Python, etc.) and familiarity with academic writing and publishing. The position does not require teaching, but it may be possible to get teaching experience
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efforts and contribute to publications in reputable academic journals. Qualifications: A PhD in Civil and Environmental Engineering or a related field High proficiency in programming languages (e.g., Python
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/ Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning libraries Excellent written and verbal communication skills Track record of publishing
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, organization of scientific workshops, and attendance at conferences. Key qualifications include a PhD in a relevant field, expertise in AI/ML (e.g., PyTorch, TensorFlow, Python), interest in materials
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computer science, mathematics, computer engineering, or relevant technical field First-author peer-reviewed published papers (or under review) Proficient programming experience in Python and libraries (e.g., Pytorch
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field, expertise in AI/ML (e.g., PyTorch, TensorFlow, Python), interest in materials applications, and a strong publication record. The position is for two years, with the possibility of renewal, subject
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Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g