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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Research Associate to conduct numerical modelling
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modelling, automated neuroanatomical phenotyping, machine learning and advanced statistical approaches. The doctoral project will be developed jointly with the successful candidate and tailored
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Summary The Department of Electrical and Computer Engineering at Ritchie School of Engineering and Computer Science at the University of Denver is looking to hire adjunct faculty to teach a variety of
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expectations: Prepare and facilitate course lectures and learning online or in-person. Maintain weekly office hours and consistent presence in assigned course(s). Model and promote critical thinking as
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include but are not limited to: AI-driven design workflows; machine learning and generative AI models; AI-based performance evaluation and simulation; agentic and multi-agent AI systems; human-AI
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assisting with statistical analysis, predictive modeling, machine learning, and quantitative research projects using trusted enterprise data. Working within the Analytics & Innovation Incubator, the intern
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(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., UR5
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BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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Prof. Igor Zozoulenko). Our focus is on: Machine-learning accelerated materials simulations ML-accelerated simulation of ion and charge carrier transport in energy materials Multiscale modeling