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of the nonlinear structural performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators
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research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet
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computationally efficient numerical structural models. To support the condition (state) assessment, the project will also explore the use of advanced estimators (e.g., Kalman Filter) or Machine Learning models
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undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
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will autonomously estimate the flexibility of converter-interfaced loads, communicate with an aggregator, and modify their decentralized control to contribute to the resilience and reliability
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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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doctoral candidate who meets the following requirements: A background and strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design
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elements such as floor slabs under service loading, enabling estimation of crack formation, joint opening, curling, and direct comparison with assumptions made in structural design calculations. The research
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to a two-year master's degree in a field related to one or more of the general areas of Computer Science, Computer Engineering, Telecommunication, Electronics. Approval and Enrolment The scholarship
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control theory, state estimation, and motion planning. You have documented experience through courses, projects or former professional work to develop and test solutions for real robotic systems You are