Website:
indirauniversity.edu.in
Job details:
Assistant Professor – Centre of Artificial Intelligence
Role Profile
Position Details
Position: Assistant Professor
Department: Centre of Artificial Intelligence
Reports To: Dean/Director/Head, Centre of Artificial Intelligence
Role Type: Teaching, Research, Training, Innovation, and University-wide AI Integration
Job Purpose
The Assistant Professor will contribute to teaching, research, innovation, capacity building, and AI adoption across the university. The role involves delivering AI-related courses, conducting interdisciplinary research, supporting faculty and students, developing AI literacy initiatives, and enabling responsible AI integration in academic and administrative functions.
Educational Qualifications
Essential
- Qualifications as per applicable UGC/AICTE/University norms.
- B.E./B.Tech. and M.E./M.Tech. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, Electronics, Robotics, Cybersecurity, or allied disciplines; OR
- Master’s Degree in AI, Computer Science, Data Science, Statistics, Mathematics, Computational Sciences, Information Technology, Computer Applications, or related fields.
Desirable
- Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Engineering, or interdisciplinary AI domains.
- UGC-NET/SET/SLET qualification where applicable.
- Publications in reputed indexed journals and conferences.
- Experience in funded projects, consultancy, patents, technology development, or AI innovation.
- Professional certifications and hands-on expertise in AI tools, Python, machine learning frameworks, cloud platforms, and Generative AI.
Required Competencies
Technical Skills
- Strong knowledge of AI, Machine Learning, Data Science, Deep Learning, NLP, Computer Vision, and Generative AI.
- Proficiency in Python and AI/ML libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, OpenCV, and Hugging Face.
- Experience with data analytics, model development, cloud AI platforms, and prompt engineering.
- Understanding of AI ethics, privacy, cybersecurity, transparency, and responsible AI practices.
Academic & Training Skills
- Ability to teach undergraduate, postgraduate, diploma, certificate, and executive programs.
- Curriculum development, instructional design, assessment creation, and project-based learning.
- Capability to conduct workshops, FDPs, AI literacy programs, and hands-on training sessions.
- Student mentoring for projects, internships, hackathons, research, patents, and entrepreneurship.
Research & Innovation Skills
- Research publication and proposal-writing capabilities.
- Ability to develop interdisciplinary AI projects and industry collaborations.
- Experience supporting innovation, patents, consultancy, and technology development.
Institutional AI Integration
- Ability to identify and implement AI applications across academic and administrative departments.
- Development of AI-enabled teaching, research, productivity, and automation solutions.
- Capacity to train faculty, staff, and students in practical AI adoption.
Experience
Essential
- Teaching, research, or industry experience in AI, ML, Data Science, Computer Science, IT, or allied areas.
- Ability to teach theory and laboratory courses in AI-related domains.
Desirable
- 1–5 years of relevant experience.
- Experience in curriculum design, AI projects, training programs, industry collaboration, research, patents, or AI laboratory development.
Key Responsibilities
Teaching & Academic Activities
- Deliver courses in AI, Machine Learning, Data Science, Python, Analytics, Generative AI, and emerging technologies.
- Develop course materials, laboratory manuals, assignments, and assessments.
- Conduct practical sessions and promote experiential learning.
- Mentor students for projects, internships, competitions, and research activities.
- Support development of new AI-focused academic programs and interdisciplinary offerings.
Research & Publications
- Conduct high-quality research and publish in reputed journals and conferences.
- Develop interdisciplinary research initiatives.
- Prepare research proposals for external funding.
- Support patents, innovation, consultancy, and industry-sponsored projects.
University-Wide AI Integration
- Facilitate AI adoption across academic schools and administrative units.
- Assist faculty in integrating AI tools into teaching, research, content development, and analytics.
- Conduct AI literacy and awareness programs for stakeholders.
- Support development of AI policies, implementation plans, and governance frameworks.
- Promote ethical, responsible, and transparent AI use.
Laboratory & Infrastructure Development
- Support establishment and operation of AI laboratories, software platforms, and computing infrastructure.
- Maintain technical resources, datasets, documentation, and learning environments.
- Coordinate with industry partners for laboratory enhancement and collaborative initiatives.
Training & Capacity Building
- Conduct faculty development programs on AI, Generative AI, data analytics, and educational technologies.
- Deliver student training programs in AI, ML, Python, and emerging technologies.
- Train non-teaching and administrative staff on AI-enabled productivity and automation tools.
- Develop structured learning resources and training materials.
Industry Collaboration & Outreach
- Build partnerships with industry, start-ups, research institutions, and government organizations.
- Facilitate internships, certifications, live projects, consultancy assignments, and collaborative programs.
- Organize conferences, workshops, hackathons, expert talks, and innovation events.
- Represent the Centre in academic and industry forums.
Institutional Responsibilities
- Assist in planning, documentation, reporting, and implementation of AI initiatives.
- Participate in committees, curriculum development, examinations, admissions, and accreditation-related activities.
- Support documentation for NAAC, NBA, NIRF, rankings, and quality assurance processes.
Expected Outcomes
- Effective delivery of AI-related academic programs.
- Enhanced AI literacy and adoption across the university.
- Increased research publications, funded projects, patents, and innovations.
- Strong industry-academia collaborations.
- Development of the Centre of Artificial Intelligence as a leading hub for teaching, research, training, and innovation.
- Improved student employability, entrepreneurship, and future-ready skills.
Key Performance Indicators (KPIs)
- Teaching effectiveness and student outcomes.
- Research publications, patents, grants, and consultancy.
- AI integration initiatives across departments.
- Training programs conducted and stakeholders trained.
- Laboratory utilization and project support.
- Industry partnerships, internships, and collaborative activities.
- Contributions to institutional development and accreditation.
Click on Apply to know more.
