Deliver lectures, tutorials, practical sessions and other teaching and learning activities in Artificial Intelligence and related areas at undergraduate and postgraduate levels.
Develop, review and enhance curriculum, course content, teaching materials and assessments to ensure academic quality and relevance to current technological and industry developments.
Supervise undergraduate and postgraduate projects, research, dissertations and/or theses, where applicable.
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Lead and deliver innovative undergraduate and postgraduate courses in Artificial Intelligence and Cybersecurity.
Develop and supervise research projects in emerging areas such as Machine Learning, Deep Learning, Ethical AI, Cyber Defence, Threat Intelligence, and Cyber Resilience.
Conduct high-quality research and publish in reputable international journals and conferences.
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Research and develop existing computer vision algorithms and incorporate novel techniques or create new algorithms from ground up to solve desired use cases
Develop and adapt advanced computer vision and state-of-the-art deep learning techniques for face recognition, object segmentation detection / classification, optical character recognition, and fraud detection
Assist in dataset preparation to enhance the models
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Solution Implementation: Translating business and operational requirements into scalable AI capabilities that automate workflows and augment decision-making.
AI Agent Integration: Integrating AI agents with observability, telemetry, event management, and operational monitoring platforms to enable intelligent automation and incident response.
Performance Optimization: Monitoring and optimizing agent performance through model evaluation, prompt refinement, and logic enhancements to improve accuracy and reliability.
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Solution Implementation: Translating business and operational requirements into scalable AI capabilities that automate workflows and augment decision-making.
AI Agent Integration: Integrating AI agents with observability, telemetry, event management, and operational monitoring platforms to enable intelligent automation and incident response.
Performance Optimization: Monitoring and optimizing agent performance through model evaluation, prompt refinement, and logic enhancements to improve accuracy and reliability.
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Design, develop, deploy, and maintain AI Agents to automate business workflows and operational processes.
Build internal AI assistants capable of handling business tasks such as document processing, knowledge retrieval, customer support, reporting, and workflow orchestration.
Integrate Large Language Models (LLMs) into business applications to enhance productivity and decision-making.
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