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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
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, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus
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supervised by Dr. Ali Trabolsi Required Education, Certifications, Licensing or Training PhD in chemistry. Preferred Education, Certifications, Licensing or Training PhD in chemistry having research topic
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, LHC , Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/01 11:59PM
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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, and evaluation The ideal candidate will lead their own project, and also collaborate with and support 1-2 PhD students on their projects. The ideal candidate will also be interested in learning to write
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit
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experience with software radios, 5G user equipment, VPNs, Tor, or other hard- and software relevant to the described systems an networks Up-to-date software development and machine learning skills, incl. work
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rigorous, collaborative research aligned with project goals. Develop and apply deep learning models, particularly in computer vision, NLP, and multimodal systems. Publish in peer-reviewed journals and
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer