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, numerical simulations, and models at different levels of complexity. Be part of change Investigation of stability in inverter-based resources and detection/mitigation of oscillatory phenomena Fundamental
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learning, and computational modelling. The doctoral candidate will investigate how pressure differences can be calculated directly from magnetic resonance imaging (MRI) and ultrasound data, reducing the need
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software that allow time-evolving models of complex systems to be calibrated against sparse, indirect, and uncertain observations. The group develops and maintains an open-source Python framework
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Information Engineering Machine Learning and Data Science Embedded Systems and hardware-oriented development Modeling and simulation of complex systems Experience with Python, MATLAB, and/or C/C++ Strong
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conjectures and intuitions proffered for the implications of new theories, providing general comparative-statics and calibration results, and working out examples and applications of models to different
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in Electrical or Mechanical Engineering, Computer Science, or a related subject. Proficiency in C++, Python, and ROS 2 is required. Strong scientific skills with proven excellence in real-life
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To be qualified for the position, you must have an MSc degree in Electrical or Mechanical Engineering, Computer Science, or a related subject. Proficiency in C++, Python, and ROS 2 is required. Strong
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the neurobiological foundations of language and auditory processing, with a particular focus on individual differences, multilingual and multiliterate experience, language aptitude, dyslexia, brain anatomy and
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research direction is the integration of strategic transport models, such as discrete choice modelling (DCM) with agent-based modelling (ABM), to examine potential transport behaviour under different
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these methods across different crops to identify conserved patterns of stress resilience 4. Identify candidate genes associated with key agronomic traits related to resilience 5. Contribute to software and web