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To apply for this position, please combine the following documents in 1 PDF and attach it under the CV column when submitting your application: Curriculum vitae A cover letter, of no more than 800 words, explaining the applicant’s past research experience and aptitude in relation to the research...
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expertise in discrete choice modelling, statistical modeling, traffic simulation, machine learning, and optimization techniques. • Strong expertise in discrete choice modelling, statistical modelling, and
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1. A PhD degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Systems Engineering, etc. 2. The candidates should have strong math, modeling, programming, and
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reacting-flow modelling. This is a one-year research appointment, with the possibility of extension subject to satisfactory research progress and funding availability. The successful candidate will work
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on integrating multimodal large language models (LLMs) with embodied AI. This position will involve the development and deployment of Vision-Language-Action models for real-world robotic applications, such as
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; 2) develop 3D models for the characterization of near-surface geological formations; 3) develop geophysical methods for imaging and characterizing subsurface structures. Key Responsibilities: Develop
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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, to develop solutions for predicting risk in international-scale financial markets. The project is developing event-triggered artificial intelligence approaches that complement existing financial risk models
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have the potential to transform medicine by providing personalised models of anatomy and physiology that support diagnosis, prognosis and treatment planning. However, creating these models currently
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learning models and are familiar with foundation models. Applicants are invited to contact Dr Ren Ge Gary at telephone number 3400 8595 or via email at [email protected] for further information