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@manchester.ac.uk . The University of Manchester The University of Manchester (www.manchester.ac.uk) enjoys a global reputation for its research and its innovative approach to learning, with an on-going £1 billion
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++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in
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friendly and international work environment Learn more about CQT at https://www.cqt.sg/ Job Description We have openings for talented early-career scientists who are ready to take up a leadership role in our
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representations developed in them as a foundation for this research activity. In this project, you will develop fundamental machine learning methods and apply them in an interdisciplinary research environment
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
and orchestration technologies for real-world logistics and decision support. Collaborate with leading experts in Artificial Intelligence and Machine Learning at ANU and Defence stakeholders. About the
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Clinic. Responsibilities include (i) supervising law students on cases and impact advocacy projects, and serving as a mentor and role model to law students in the clinics; (ii) helping to design and teach
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administration or data analytics, such as Applied Psychology, Organisational Behaviour, Statistics, Machine Learning, and so on; Excellent oral and written communication skills in English, including the ability
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 2 months ago
team in the AI in Medicine Lab (www.aimlab.ca ). This position is based in the School of Biomedical Engineering. The successful candidate will work in the AI in Medicine Lab, applying machine learning
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. The core research objective of this PhD is to design and evaluate “latency hiding” methods for immersive networked interactions. This involves (i) developing predictive machine learning models that forecast