Teacher Artificial Intelligence

Roles and responsibilities

The selected candidate will have primary research and teaching interests in artificial intelligence courses. The position involves teaching at the undergraduate level, with robust engagement in practice and collaboration with the business community. The successful candidate will be appointed to the Bachelor of Science in Artificial Intelligence Program and may collaborate with other programs within the Information Technology department.

Qualifications & Experience

• Ph.D. in Artificial Intelligence, Machine Learning, or related fields from an internationally reputable university.
• Outstanding research record in artificial intelligence, demonstrated by publications in top international journals and conferences (Scopus and SCIE).
• Proven excellence in teaching, curriculum development, and learning outcome assessment.
• Experience in teaching courses such as Machine Learning, Deep and Reinforcement Learning, Natural Language Processing, Computer Vision and Pattern Recognition, and Artificial Intelligence Fundamentals at the undergraduate level.
• Demonstrated ability to collaborate effectively with colleagues in professional service.
• Proficiency in English with excellent communication skills.
• Strong interpersonal skills.
• Industrial experience in providing statistical consultancy to researchers and the public.
• Openness to cross-disciplinary cooperation in research and teaching.
  

Essential Duties And Responsibilities

The selected applicant will be expected to:

• Develop and teach undergraduate courses in Artificial Intelligence and Computer Science.
• Engage in innovative, technology-based approaches to learning and teaching.
• Publish high-quality research in leading internationally recognized journals within their field.
• Participate in departmental, college, and university committees as assigned.
• Actively contribute to promoting the growth of Ajman University.
• Provide consultancy services to researchers and the business community.
• Continuously seek methods, procedures, and resources to effectively achieve course and lesson objectives.
• Perform miscellaneous job-related duties as assigned.

Desired candidate profile

1. Expertise in Artificial Intelligence and Machine Learning

• Foundational Knowledge: Deep understanding of core AI concepts, including machine learning, deep learning, reinforcement learning, natural language processing, computer vision, robotics, and expert systems.
• Advanced AI Techniques: Proficiency in advanced AI algorithms and models, including neural networks, support vector machines, decision trees, Bayesian networks, and generative adversarial networks (GANs).
• Mathematical and Statistical Knowledge: Strong background in the mathematical foundations of AI, including linear algebra, probability theory, statistics, optimization, and calculus.
• AI Frameworks and Tools: Expertise in widely-used AI frameworks and libraries such as TensorFlow, PyTorch, Keras, scikit-learn, OpenAI Gym, and others for implementing machine learning models and AI solutions.

2. Teaching and Curriculum Development

• Course Design: Designing and teaching undergraduate and graduate courses in artificial intelligence, machine learning, data science, natural language processing, and other AI-related topics.
• Active Learning: Implementing innovative teaching methods, such as flipped classrooms, project-based learning, and hands-on coding exercises, to engage students and foster a deeper understanding of AI concepts.
• Graduate Supervision: Supervising graduate students (Master's and Ph.D.) in their AI-related research projects, theses, and dissertations. Guiding them through the development and implementation of AI models and experiments.
• Advising and Mentoring: Providing academic and career advising to students, helping them navigate course selections, research opportunities, and career paths in AI-related industries.
• Assessment and Feedback: Creating assessments that test theoretical understanding as well as practical application, and providing constructive feedback to students.

3. Research and Scholarly Activity

• Independent Research: Leading independent, cutting-edge research in AI, exploring novel algorithms, architectures, and techniques that contribute to advancing the field.
• Interdisciplinary Research: Collaborating with researchers from other fields (e.g., healthcare, robotics, economics, neuroscience) to apply AI methods to solve complex, interdisciplinary problems.
• Research Publications: Publishing high-quality research in top-tier peer-reviewed journals and conferences in the AI field, such as NeurIPS, ICML, CVPR, and AIJ (Artificial Intelligence Journal).
• Research Funding: Securing funding for research projects through grant proposals to government agencies, private foundations, and industry partners. Managing the budget and timeline of funded research projects.
• AI Ethics and Fairness: Conducting research on the ethical implications of AI technologies, including fairness, bias mitigation, transparency, privacy concerns, and the societal impact of AI.

4. Industry Collaboration and Application

• Collaborative AI Projects: Partnering with industry stakeholders to work on real-world AI applications, including AI solutions for healthcare, finance, autonomous systems, natural language processing, and smart cities.
• Technology Transfer: Engaging in technology transfer activities, which may include patenting, licensing, and working with industry partners to commercialize research findings and AI technologies.
• AI Consultancy: Providing AI consultancy to companies or organizations seeking expertise in AI model development, data analysis, and strategic implementation of AI solutions.
• Internships and Co-ops: Facilitating industry internships and cooperative education programs that connect students with companies and allow them to gain hands-on experience in AI applications.

5. Supervision and Mentorship

• Ph.D. Supervision: Overseeing Ph.D. students in AI research, helping them refine research questions, develop methodologies, publish papers, and prepare for academic or industry careers.
• Research Group Leadership: Leading a research group, managing research assistants, postdoctoral researchers, and other collaborators, and driving the direction of the group’s research activities.
• Interdisciplinary Supervision: Guiding students and researchers who work on interdisciplinary AI projects, such as combining AI with healthcare, finance, robotics, or environmental science.

6. Contribution to Academic Programs and University Service

• Curriculum Leadership: Contributing to the development and evolution of AI-related academic programs, ensuring that the curriculum remains aligned with the latest developments in AI and industry needs.
• Program Accreditation: Assisting in the accreditation process for AI and computer science programs, ensuring that the curriculum meets the standards of accrediting bodies (e.g., ABET, AACSB).
• Departmental Leadership: Taking on leadership roles within the department, such as chairing committees, participating in hiring decisions, and developing departmental strategies for growth and innovation.
• University Service: Serving on university committees, participating in faculty governance, and contributing to institutional development, diversity, and community-building activities.

7. Conference Participation and Professional Development

• Conference Presentations: Presenting research at international and national AI conferences and workshops, engaging with peers to exchange ideas and stay up-to-date with the latest developments in AI.
• Organizing Events: Organizing or co-organizing workshops, seminars, or special sessions at conferences focused on key areas of AI research or application.
• Lifelong Learning: Continuously pursuing professional development through online courses, workshops, and attending AI-related conferences to stay at the forefront of the field.
• Peer Review: Reviewing research papers for leading AI journals and conferences, contributing to the quality control and advancement of the field.