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-doctoral research position under the supervision of Dr. Chris Smith Home | Chris Smith . Our lab studies spatial population genetics, using simulation-based inference and machine learning to infer
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, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
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scientific leaders and researchers. The group of Wang Zhongjian is looking for postdocs working on scientific computing and machine learning related topics. The funding is currently under a MOE grant entitled
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Challenge grant. The successful candidate will work closely with the Principal Investigators (PIs) to develop and implement innovative research integrating machine learning, computer vision, and wildlife
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-science and signal-analysis tasks, including processing experimental signals, integrating datasets, developing machine-learning models, and mapping measured fuel properties to SAF performance. For the post
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statistical methodology, including genomic prediction, crop simulation and machine learning, to improve prediction of crop yield and related traits. Supervision and Researcher Development: Assist with mentoring
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(DFT) simulations and develop machine learning potentials to investigate zeolite-related systems. The role will focus on delivering research projects and promoting research excellence in this area. The
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analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional team members to develop hypotheses, interpret data, and
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reference monitor on top of seL4 for the secure containment of AI agents. We will develop new mechanisms for dynamically controlling agents’ capabilities and information flows, together with machine-checked
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representation through machine learning. The position is for a fixed term of 3 years and is part of the project “Reaching AI Projections Trustworthy for Unseen Rainfall Extremes (RAPTURE)”, funded by a European