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++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in
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27 Mar 2026 Job Information Organisation/Company Télécom Paris Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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, designing, implementing, and evaluating ML models that address practical challenges across domains. The researcher will contribute to the development of a full machine learning pipeline, including data
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 1 hour ago
. Experience with technical software such in the fields of design, construction and/or building operations. Including programs such as: Dropbox, Microsoft Office Suite, 3D Modeling, and willingness to learn new
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 15 days ago
was installed at IT4Innovations in 2025. For more details, see www.it4i.eu . Activity description: · modelling and optimization of electrical networks using open source tools (preferably Julia or Python
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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discipline. Experience with deep learning framework PyTorch or similar. Strong background in machine learning, image or signal processing. Knowledge of SotA models for multi-modality and scene understanding
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models, and ensuring students have a structured and engaging learning experience. Career Readiness Competencies: Access & Opportunity Leadership Professionalism Essential Functions Teach assigned courses
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the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model