Job Summary
We are seeking a highly motivated and qualified Assistant Professor – Computer Science to join our academic team. The candidate will be responsible for teaching undergraduate and/or postgraduate students, developing course content, conducting practical sessions, guiding student projects, and contributing to research, academic administration, and institutional development.
Key Responsibilities
1. Teaching & Academic Responsibilities
- Deliver engaging lectures, tutorials, and practical/laboratory sessions in Computer Science.
- Prepare lesson plans, course materials, presentations, assignments, and question papers.
- Conduct internal assessments, examinations, evaluations, and provide timely feedback.
- Ensure effective delivery of the prescribed curriculum as per University guidelines.
- Use innovative teaching methods, technology, and practical examples to enhance student learning.
- Maintain accurate academic and student records.
2. Student Development
- Mentor and guide students regarding academics, projects, internships, and career development.
- Supervise student projects, seminars, presentations, and technical activities.
- Support students in participating in hackathons, coding competitions, technical events, and conferences.
- Provide academic counselling and maintain regular communication with students.
3. Practical & Technical Responsibilities
Depending on specialization, the faculty member may handle subjects such as:
- Programming / Object-Oriented Programming
- Data Structures & Algorithms
- Database Management Systems
- Operating Systems
- Computer Networks
- Software Engineering
- Web Technologies
- Artificial Intelligence & Machine Learning
- Data Science
- Cloud Computing
- Cyber Security
- Computer Architecture
- Python / Java / C / C++
- Emerging technologies and other Computer Science subjects.
4. Research & Development
- Conduct and publish quality research in reputed journals/conferences.
- Participate in research projects, consultancy, and funded research activities.
- Encourage students to undertake research and innovation projects.
- Contribute to patents, copyrights, research proposals, and academic collaborations where applicable.
5. Department & Institutional Responsibilities
- Participate in departmental meetings and academic planning.
- Contribute to curriculum development and revision.
- Assist in accreditation and compliance activities such as NAAC/NBA/University requirements, as applicable.
- Coordinate academic events, workshops, seminars, FDPs, and technical activities.
- Perform examination, admission, committee, and other responsibilities assigned by the University/Institute.
Educational Qualification
- Master's Degree (M.E./M.Tech./M.Sc./MCA or equivalent) in Computer Science / Computer Engineering / Information Technology or a relevant discipline from a recognized University/Institution.
- Ph.D. in Computer Science/Engineering or relevant area will be preferred.
- Candidates should fulfil the applicable UGC/University/Regulatory Authority eligibility requirements.
Experience
- Freshers with strong academic credentials may be considered.
- Prior teaching experience in a University/College/Engineering/Management/Computer Science institution will be preferred.
- Industry experience in relevant technology areas will be an added advantage.
Required Skills
- Strong knowledge of Computer Science fundamentals.
- Excellent teaching and presentation skills.
- Good command of programming languages and technical concepts.
- Ability to use modern teaching tools and Learning Management Systems.
- Strong mentoring and student-handling skills.
- Research and academic writing skills.
- Good communication and interpersonal skills.
- Ability to work collaboratively within an academic team.
- Good documentation and academic administration skills.
Preferred Skills / Specialization
Candidates with expertise in any of the following areas will be preferred:
Artificial Intelligence | Machine Learning | Data Science | Cyber Security | Cloud Computing | IoT | Blockchain | Software Engineering | Full-Stack Development | Database Technologies | Computer Networks | NLP | Computer Vision
Key Performance Areas (KPIs)
- Quality of teaching and student feedback.
- Course completion and academic performance.
- Student mentoring and project guidance.
- Research publications and research projects.
- Participation in institutional activities.
- Development of innovative teaching practices.
- Contribution to accreditation and academic documentation.
- Student participation in technical/research activities.
Personal Attributes
- Passion for teaching and learning.
- Professional and disciplined approach.
- Positive attitude and willingness to learn emerging technologies.
- Strong academic integrity.
- Ability to mentor and motivate students.
- Commitment to institutional goals and continuous improvement.
Contact :
Rinkal Kothiya
98249 45442
[Confidential Information]
