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Field
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ideas from machine learning, econometric choice modelling and mathematical psychology. You will investigate how large language models, optimisation algorithms and automated model search methods can
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mathematical or computational algorithms. Strong scientific programming skills. Evidence of the ability to conduct research independently and to identify and address challenging research questions. Evidence of
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validate wearable data algorithms, software tools and pipelines supporting large-scale, multi-cohort research. It will contribute to the ProPASS federated data analysis platform, including testing
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sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for Tunnel Boring Machine (TBM) tunnelling and excavation Developing large language model enhanced
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for drug target discovery, computational biology, advanced bioinformatics, and novel AI algorithms for identifying drug targets in complex diseases such as chronic kidney disease, idiopathic pulmonary
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for partial differential equations, and multiscale partial differential equations. The candidate will develop efficient numerical methods for solving the problems, and implement the numerical algorithms
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collaborative research on humanoid robotics, including simulation, motion generation, and control Develop and implement algorithms leveraging computer graphics techniques (e.g., physics simulation, character
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algorithm code base including noise reduction, acoustic echo cancellation, automatic gain control, voice activity detection, packet loss compensation and other audio enhancements Software development of new
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applications for a Postdoctoral Fellow to join an international research team on the Marsden Fund project Scalable Bayesian Algorithms for Multi-Physics Inverse Problems with High-Level Representations
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/ The research fellow will work closely with PI Patrick Rebentrost on developing novel quantum algorithms