Faculty Member; as per UGC Cadre - Computer Science, AI & Machine Learning

Position: Faculty Member (as per UGC Cadre) -  Computer Science, AI & Machine Learning
Role Overview
Atlas Skill Tech University invites applications from dynamic academicians, researchers, and industry practitioners in Computer Science, Artificial Intelligence, Machine Learning, and allied domains. The selected faculty will anchor advanced courses in AI/ML, Deep Learning, NLP, Generative AI, and Data Science while driving cutting-edge research and industry-linked innovation. As part of the vibrant uGDX School of Technology, you will mentor India's next generation of AI engineers and contribute to a research ecosystem shaped by IEEE and ACM standards of excellence.
Specialisation Areas (any one or more)
Artificial Intelligence & Machine Learning
Deep Learning, Neural Networks & Computer Vision
Natural Language Processing & Large Language Models (LLMs)
Generative AI, Foundation Models & Responsible AI
Data Science, Big Data Analytics & Business Intelligence
Reinforcement Learning & Autonomous Systems
Cloud-Native AI, MLOps & AI System Design
Algorithms, Theory of Computation & Software Engineering
Cybersecurity, Privacy & Trustworthy AI

Key Responsibilities
Teaching & Curriculum Delivery
Deliver undergraduate and postgraduate courses aligned with BTech CS (AI & ML) and allied programmes.
Develop Outcome-Based Education (OBE) curriculum benchmarked against industry trends and NEP 2020.
Conduct laboratory sessions, hands-on project workshops, hackathons, and capstone thesis supervision.
Integrate real-world case studies, problem-based learning, and industry-grade project methodologies.
Research & Innovation
Conduct high-quality research and publish in Scopus, SCI, ABDC, IEEE, ACM, or UGC-CARE indexed venues.
File patents, develop functional prototypes, and contribute to technology commercialisation and start-up ecosystems.
Pursue funded research grants (DST, SERB, AICTE, DBT, industry grants) and interdisciplinary collaborations.
Contribute to the School's research output and citation impact.
Industry Collaboration
Build partnerships with technology companies, startups, and national/international research organisations.
Facilitate student internships, live projects, industry mentorship sessions, and innovation challenges.
Organise workshops, conferences, bootcamps, and invited guest lectures.
Support the Atlas incubation ecosystem and entrepreneurship initiatives.
Student Mentoring
Guide student research projects, competition teams, and innovation showcases.
Mentor students for higher studies, entrepreneurship, and career development pathways.
Encourage participation in national and international technical events and olympiads.
Academic & Institutional Contribution
Participate in NAAC/NBA accreditation, curriculum review, academic planning, and quality assurance.
Contribute to departmental growth, institutional outreach, and strategic initiatives of uGDX School of Technology.

Qualification Requirements
Essential
Ph.D. in the relevant discipline (see above) from a recognised university/institute.
B.E./B.Tech and M.E./M.Tech with consistently strong academic credentials.
Demonstrated research output: publications, patents, or funded projects.
Preferred / Desirable
Industry / R&D experience in a relevant technology domain.
Strong publication, patent, or externally funded project record.
Experience in interdisciplinary and experiential/project-based education.
Hands-on experience with LLM fine-tuning, RAG pipelines, or AI product development (strongly preferred).
Familiarity with AI ethics frameworks, explainability tools, and fairness-aware ML (preferred).
Technical Skills
Technical skill sets from any of this domain:

* AI, Machine Learning, Deep Learning, Generative AI & LLMs

* Robotics, ROS, Computer Vision & OpenCV

* Python, C++, Java

* AWS, Azure, GCP, MLOps

* Git, Docker, Kubernetes

* IoT & Edge Computing

Desired Competencies
Excellent communication, presentation, and classroom delivery skills.
Research and innovation mindset with a track record of output.
Industry engagement and professional networking capability.
Ability to mentor multidisciplinary and diverse student cohorts.
Passion for emerging technologies and future-focused, outcome-driven education.
Key Performance Indicators (KPIs)
Student learning outcomes, course…