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Predoctoral Researcher (PhD Candidate) in Computational Simulation and AI for Therapeutic Ultrasound
PID2024-163008OB-I00, focused on the development of computational simulation and artificial intelligence tools for Magnetic Resonance-guided Focused Ultrasound (MRgFUS). The selected candidate will work
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group led by Prof. Dr. Leticia Tarruell. The group performs quantum simulations with ultracold quantum gases, using atoms to engineer novel forms of quantum matter and to solve problems that are hard
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) an honours degree in the discipline related to transport/logistics modeling and simulation or an equivalent qualification; (b) experience in using one of the software, including STATA, Python, R or Matlab
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evaluation of student achievement of competencies in both student clinical practicums and clinical skills and simulation laboratory experiences. This individual will collaborate with program faculty and skills
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Computationally efficient modelling & simulation and applications
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Responsibilities Develop cloud-based pipelines to process robotic/ATS survey data Build AI/analytics models for alignment, deflection, and tolerance control Design real-time dashboards and alert systems Develop BIM
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scale over molding experiments with natural fiber materials Characterize fiber distribution, adhesion, mechanical properties, and barrier performance Develop and integrate simulation models for material
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addresses the "calibration problem" in particulate continuum models and particle simulations. Specifically, it focuses on developing robust methodologies for selecting and parameterising contact models, a
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, uncertain, and multi-dimensional nature of student learning behaviours. This research introduces quantum-inspired representations and optimisation techniques to model student engagement, performance
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individual to join the digital behavioural insights lab (DBI) as a Research Fellow. Our focus is on building digital health simulation models and interventions and cardiometabolic disease prevention and