Associate Professor in General Artificial Intelligence, with a specialization in Machine Learning (ML) and Deep Learning (DL). The selected candidate will play a key role in shaping the future of AI education and research, contributing significantly to the undergraduate Artificial Intelligence program.

We seek candidates with a strong academic and research background in AI, capable of inspiring undergraduate students, conducting cutting-edge research, and building strong industry partnerships.

Key Responsibilities:

• Design and deliver high-quality undergraduate courses in Artificial Intelligence, Machine Learning, and Deep Learning, ensuring strong conceptual and practical understanding.
• Develop hands-on learning experiences using real-world datasets, open-source AI tools, and frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Mentor and guide students through research projects, final-year capstones, and innovation-based assignments aligned with current industry trends.
• Continuously update curriculum content to reflect the latest advancements in AI and prepare students for evolving roles in technology and research sectors.
• Conduct impactful research in core AI areas and involve undergraduate students in research labs, internships, and publications.
• Build connections with industry to create opportunities for student internships, project collaborations, and career pathways.
• Promote responsible and ethical AI practices by integrating fairness, transparency, and bias mitigation into teaching and project work.
• Support departmental academic activities, such as organizing student workshops, AI competitions, and community outreach programs to enhance student engagement.

Required Qualifications:

• PhD in Artificial Intelligence, Computer Science, Data Science, or a closely related field.
• Strong research record in ML/DL with publications in top-tier AI venues.
• Proven experience in undergraduate teaching and curriculum development.
• Ability to supervise research and lead academic projects.
• Evidence of securing or contributing to research grants.

Preferred Qualifications:

• Experience in interdisciplinary AI applications (e.g., healthcare, robotics, finance, NLP, computer vision).
• Prior collaboration with industry or government on AI projects.
• Demonstrated leadership in academic or research environments.
• Familiarity with ethics, bias mitigation, and fairness in AI systems.