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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will
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or use existing simulation platforms to validate the developed algorithms and models. Analyse simulation data, and create visualizations to support research findings. Design and build prototypes
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particular sequential, multiple assignment, and randomized trial design. You will have the opportunity to mentor the PhD students on the team. Experience in any of the following areas may be useful: SMART
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develops new intellectual understanding Disseminate research findings for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate
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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning and deep learning algorithms for dynamic systems (sequential or time-series data). Experience
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. Develop and implement control algorithms for distributed multi-agent system operations and spacecraft-based robotic manipulation. Perform research on spacecraft dynamics and control, including trajectory
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information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms
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properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 14th August 2025 Languages English English English PhD Research Fellow in Supervisory Control for the Power Grid of a
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why this PhD topic fits their interest/background. This statement of research interest should not exceed one page Desired qualifications: Good knowledge in programming language theory, algorithms
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond