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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in
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Intelligence, Computational Linguistics, Data Science, or a closely related field Strong programming skills, e.g., Python, and familiarity with machine learning and/or software engineering workflows; experience
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the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago
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models to characterize agricultural and ecological systems; Experience in applying advanced Artificial Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in
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Networks. Knowledge of and experience in Python, TensorFlow, Keras, or other Machine Learning toolboxes, is essential. Knowledge of and experience in Large Language Models is highly relevant. The successful
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going to our job site (https://cfopitt.taleo.net/careersection/pitt_faculty_external/jobsearch.ftl ), searching job code 25005706 in the keyword search, and submitting your materials through our Pitt
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of roles and tasks. Strict expertise in all the technologies is not required. However, a great attitude and willingness to learn is a must. Flexible Work location The selected candidate will offer
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9 Jan 2026 Job Information Organisation/Company Consejo Superior de Investigaciones Cientificas Department Centre for Automation and Robotics (CAR) Research Field Engineering Researcher Profile
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, individualized education. Faculty are committed to creating a student-centered learning community that embraces multiple viewpoints. It is a department in which learning, research, and professional activity inform