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Responsibilities: Undertake research on algorithms and data systems for next-generation data preparation and data cleaning for data analytics. Produce research papers, reports, and presentations as required by
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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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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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or use existing simulation platforms to validate the developed algorithms and models. Analyse simulation data, and create visualizations to support research findings. Design and build 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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Responsibilities: Development of stochastic and analytical methods for nonlinear partial differential equations Implementation of relevant numerical experiments using deep learning algorithms Job Requirements: PhD
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lecturing, small-group teaching, and tutoring of undergraduates and graduate students. Job Requirements: Essential Criteria Candidates must have a PhD (or be near completion) in Computer Science