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Field
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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) optimise BIM software performance and address challenges, including model processing, data storage, and rendering efficiency; and (e) collaborate with AI algorithm teams to understand the business
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techniques which have traditionally been employed. As artificial intelligence becomes increasingly ingrained in the society, it is crucial to ensure that the machine learning algorithms not only make correct
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computer programming to verify the efficiency of the designed solution algorithms Analyze data acquired from the field survey Develop machine learning models for prediction and recommendation Job
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Information Engineering and Media to develop Machine Learning and AI algorithms for real-world and media-related applications. The Research Associate/Research Fellow is also expected to support teaching
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements. § Implementing algorithms
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innovative ideas to enhance existing algorithms and frameworks. Analyse and interpret findings, ensuring scientific rigour and practical relevance. Prepare and submit manuscripts to leading conferences and
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objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms (50%). PhD in computer science, engineering