Assistant Professor - Centre of Artificial Intelligence

Indira University; Pune District; On-site; INR 800,000 - 1,200,000; Full time

Job summary

Indira University is seeking an Assistant Professor for the Centre of Artificial Intelligence in Pune, Maharashtra. The role emphasizes teaching, research, and AI integration into university functions. Candidates should have a Ph.D. in a relevant field and substantial experience in AI, along with strong teaching skills.

This position offers opportunities for developing innovative AI programs and contributing to a dynamic academic environment focused on research and training.

Qualifications

• Experience in AI, ML, Data Science, or related fields.
• Strong publication record in reputed journals and conferences.
• Professional certifications in AI tools and frameworks.

Responsibilities

• Deliver courses in AI and related fields.
• Conduct high-quality research and publish findings.
• Support interdisciplinary projects and innovation initiatives.

Skills

AI

Machine Learning

Data Science

Deep Learning

Python

NLP

Computer Vision

Generative AI

Education

B.E./B.Tech. and M.E./M.Tech. in relevant fields

Ph.D. in AI or related fields

UGC-NET/SET/SLET qualification

Tools

NumPy

Pandas

TensorFlow

PyTorch

OpenCV

Hugging Face

Job description

Assistant Professor – Centre of Artificial Intelligence

Role Profile

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

• 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.
• 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.

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 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

• 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.
• 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.
• 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.
• 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.
• Training programs conducted and stakeholders trained.
• Laboratory utilization and project support.
• Industry partnerships, internships, and collaborative activities.
• Contributions to institutional development and accreditation.