Assistant Professor - Centre of Artificial Intelligence

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.