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Field
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, use imitation learning algorithms to learn pick-and-place actions, design HRI experiments with users, evaluate data, and share the code and benchmarks in open repositories. This postdoctoral position is
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candidate will demonstrate a record of excellence in one or more core areas of quantum information, such as quantum computing, quantum algorithms, quantum simulation, quantum networks, or quantum sensing
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for the aforementioned reactions. Based on the automatic reactor, an I-TR-NUS&TR-L running benchtop spectrometer, and machine learning algorithms, we will be able to achieve a higher yield and control the reaction to stop
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simulations and data analysis. This includes data analysis using Python-based algorithms. Experience with EELS is preferred. Skills This See Experience
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learning algorithms. Expertise in object-oriented programming, scripting languages, and modern software engineering practices for research codes. Demonstrated effective written and oral communication skills
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Develop event-driven algorithms and software components for autonomous experiment control and adaptive image acquisition Build scalable, maintainable, and open-source software for high-throughput image
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the project. What you will do Conduct original and high-quality research in machine learning and computer vision; Develop novel algorithms for adapting and specialising visual foundation models; Publish
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to quantify the impacts of new component technologies, control algorithms and powertrain architectures with focus on advanced technologies. The candidate will assist on projects to benchmark next generation
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; Develop novel algorithms for adapting and specialising visual foundation models; Publish research findings at leading machine learning and computer vision venues such as CVPR, ICCV, ECCV, NeurIPS, and ICLR
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codes and process their results. Helping to develop new models and algorithms to simulate pulse propagation, the material response, and other aspects of our experiments. Coding in Julia and python. Take a