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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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of fairness, safety, and privacy in digital technologies. Key Responsibilities: Conduct research and development in trust technologies – translating algorithms into tools and frameworks and implementing working
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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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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably Bachelor’s degree in Computer Engineering, Computer
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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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Responsibilities: Designing and developing scalable algorithms for building Data+AI systems. Writing research papers of high quality based on research results Building deployable Data+AI systems based
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literature review, algorithm design, experiment design, model training, evaluation, and benchmarking. Work with and supervise undergraduate or graduate student assistants, guiding them in data collection
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algorithms Evaluate performance, interoperability, and security implications of replacing classical cryptographic schemes with quantum-safe alternatives Support the development of technical documentation
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ethical and security standards. Concept and Algorithm Development: Innovate in data science, machine learning, and AI. Data Analysis and Reporting: Contribute to data analysis, reporting, and publication