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are particularly interested in: machine learning for molecular and omics data, including representation learning for biological sequences and structures, and the integration of multiple omics layers machine learning
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partners to apply findings. You will also help recruit and support your linked PhD student and participate in the programme's mentoring, learning and international activities. Skills and experience You will
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Australasia. More than 9,000 students study across our ten schools and departments, learning from internationally recognised educators and researchers. Our staff and students can connect with our flagship
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 9 hours ago
learning experience focused on the evolving global landscape of generic drug regulation, manufacturing, and supply chain dynamics. The research experience emphasizes comparative evaluation of international
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Schemes of Service: Research Division: Infocomm Technology Employment Type: Fixed Term As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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areas of statistics, data science, and artificial intelligence (AI). The position will focus on developing and applying novel statistical, machine-learning, and AI methods to advance biomedical and
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on cybersecurity that leads
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, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural