Assistant Professor of Computer Science

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

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• Deliver engaging lectures, tutorials, and practical/laboratory sessions in Computer Science.
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• Prepare lesson plans, course materials, presentations, assignments, and question papers.
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• Conduct internal assessments, examinations, evaluations, and provide timely feedback.
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• Ensure effective delivery of the prescribed curriculum as per University guidelines.
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• Use innovative teaching methods, technology, and practical examples to enhance student learning.
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• Maintain accurate academic and student records.
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2. Student Development

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• Mentor and guide students regarding academics, projects, internships, and career development.
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• Supervise student projects, seminars, presentations, and technical activities.
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• Support students in participating in hackathons, coding competitions, technical events, and conferences.
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• Provide academic counselling and maintain regular communication with students.
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3. Practical & Technical Responsibilities

Depending on specialization, the faculty member may handle subjects such as:

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• Programming / Object-Oriented Programming
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• Data Structures & Algorithms
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• Database Management Systems
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• Operating Systems
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• Computer Networks
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• Software Engineering
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• Web Technologies
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• Artificial Intelligence & Machine Learning
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• Data Science
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• Cloud Computing
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• Cyber Security
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• Computer Architecture
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• Python / Java / C / C++
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• Emerging technologies and other Computer Science subjects.
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4. Research & Development

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• Conduct and publish quality research in reputed journals/conferences.
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• Participate in research projects, consultancy, and funded research activities.
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• Encourage students to undertake research and innovation projects.
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• Contribute to patents, copyrights, research proposals, and academic collaborations where applicable.
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5. Department & Institutional Responsibilities

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• Participate in departmental meetings and academic planning.
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• Contribute to curriculum development and revision.
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• Assist in accreditation and compliance activities such as NAAC/NBA/University requirements , as applicable.
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• Coordinate academic events, workshops, seminars, FDPs, and technical activities.
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• Perform examination, admission, committee, and other responsibilities assigned by the University/Institute.
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Educational Qualification

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• 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.
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• Ph.D. in Computer Science/Engineering or relevant area will be preferred.
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• Candidates should fulfil the applicable UGC/University/Regulatory Authority eligibility requirements.
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Experience

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• Freshers with strong academic credentials may be considered.
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• Prior teaching experience in a University/College/Engineering/Management/Computer Science institution will be preferred.
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• Industry experience in relevant technology areas will be an added advantage.
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Required Skills

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• Strong knowledge of Computer Science fundamentals.
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• Excellent teaching and presentation skills.
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• Good command of programming languages and technical concepts.
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• Ability to use modern teaching tools and Learning Management Systems.
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• Strong mentoring and student-handling skills.
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• Research and academic writing skills.
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• Good communication and interpersonal skills.
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• Ability to work collaboratively within an academic team.
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• Good documentation and academic administration skills.
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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)

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• Quality of teaching and student feedback.
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• Course completion and academic performance.
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• Student mentoring and project guidance.
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• Research publications and research projects.
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• Participation in institutional activities.
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• Development of innovative teaching practices.
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• Contribution to accreditation and academic documentation.
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• Student participation in technical/research activities.
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Personal Attributes

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• Passion for teaching and learning.
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• Professional and disciplined approach.
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• Positive attitude and willingness to learn emerging technologies.
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• Strong academic integrity.
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• Ability to mentor and motivate students.
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• Commitment to institutional goals and continuous improvement.
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Contact :

Rinkal Kothiya

98249 45442

[email protected]