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, Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/02 04:59 AM
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their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master
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middleware (e.g., ROS, MoveIt) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g
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some pedagogical training. In addition to research, the position includes teaching, supervision, and other teaching-related tasks amounting to 20% of the working time. What we offer As a Postdoc you are
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consideration will be made to candidates with experience in automation or machine learning. The postdoc will join a group which is focused on pioneering applications of modern machine learning methods, FAIR data
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next generation of scientists and build a workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
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website: https://cruchagalab.wustl.edu/ . Research Projects: Plasma, CSF and Brain Proteomic analysis. Biomarker identification through the use of machine learning and AI approaches. Integration
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at the intersection of educational data science, AI in education, and the learning sciences, with additional advisory support from faculty and researchers across learning sciences, computer science, machine learning
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, dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand principles and mechanisms underlying distributed brain network computations through the dual