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Ph.D. in Computer Science and Engineering

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Level
Ph.D.
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Duration
As per UGC Guidelines
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Ph.D. in Computer Science and Engineering

Admission Procedure

Merit prepared on basis of the qualifying exam

Provisional Admission

Master’s Degree Holders: Master’s degree with 55% marks or equivalent. 5% relaxation for SC/ST/OBC (NCL)/PwD/EWS.

facilities Scheme of Teaching and Evaluation

About The Program

Welcome to the PhD in Computer Science program at Graphic Era Deemed to be University, one of the most comprehensive and research-intensive programs for aspiring computer scientists, academicians, and industry experts.

With the rapid evolution of digital technologies and their growing role in shaping industries and societies, there is a pressing need for researchers who can contribute novel solutions to complex computational challenges.

As one of the best Universities for PhD in Computer Science in India, Graphic Era offers a robust environment for innovation, critical thinking, and interdisciplinary research. Whether your interest lies in Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, Cybersecurity, Blockchain, Data Science, Big Data Analytics, Software Engineering, or Algorithms, this program provides the tools, mentorship, and exposure necessary to make a lasting impact in both academia and industry.

Eligibility

  • Master’s Degree Holders: Master’s degree with 55% marks or equivalent. 5% relaxation for SC/ST/OBC (NCL)/PwD/EWS.
  • Bachelor’s Degree Holders: 4-year/8-semester Bachelor’s degree with 75% marks. 5% relaxation for reserved categories
  • Final-Semester Students: Candidates awaiting final results may also apply.

Note: All eligibility conditions as per AICTE/UGC regulations in force.

Teaching Pedagogies

The Ph.D. program adopts advanced, research-centric teaching pedagogies aimed at developing independent, ethical, and innovative researchers. The pedagogical framework emphasizes inquiry, experimentation, mentorship, and scholarly dissemination to foster critical thinking and original contributions to knowledge. Learning is facilitated through research supervision, seminars, collaborative projects, experiential activities, and digital research platforms.

  • Research-Oriented Pedagogy

    Emphasis on learning through original research, problem identification, hypothesis formulation, experimentation, and validation.

  • Inquiry-Based Learning

    Scholars are encouraged to critically analyze existing literature, question established theories, and explore research gaps.

  • Mentor–Mentee Pedagogy

    One-to-one guidance through regular interactions with supervisors and doctoral advisory committees to ensure continuous research progress.

  • Seminar-Based Learning

    Learning through research seminars, proposal presentations, progress reviews, and pre-submission defenses.

  • Project-Based Learning

    Hands-on research projects involving model development, system design, algorithm implementation, and experimental evaluation.

  • Experiential Learning

    Learning by doing through simulations, lab experiments, field studies, case analysis, and real-world problem solving.

  • Collaborative Learning

    Interdisciplinary and team-based research through group discussions, joint publications, and collaborative projects.

  • Blended and Digital Learning

    Use of online research tools, MOOCs, virtual labs, digital libraries, research databases, and advanced software platforms.

  • Publication-Oriented Learning

    Learning through preparation of journal papers, conference publications, patents, and technical reports.

Program Educational Objectives (PEOs)

PEO1

To produce students employable towards building a successful career based on sound understanding of theoretical and applied aspects as well as methodology to solve multidisciplinary real-life problems.

PEO2

To produce professional graduates ready to work with a sense of responsibility, ethics and enabling them to work efficiently individually and also as a team.

PEO3

To impart the competency in students so that they are able to pursue higher studies and research in areas of engineering and other professionally related fields.

PEO4

To inculcate ability to adapt to the changing technology through continuous learning.

Specializations

  • AI & Machine Learning, Deep Learning, NLP
  • Cloud, Distributed & Parallel Computing
  • Cyber Security, Blockchain, Network Science
  • Computer Vision, Image Processing
  • Explainable AI, Recommender Systems, Bioinformatics
  • Robotics, Quantum Computing, IoT, 5G/6G
  • Multicore and High-Performance Computing, Software Engineering

Program Outcomes (POs)

PO1

An ability to independently carry out research /investigation and development work to solve practical problems.

PO2

An ability to write and present a substantial technical report/document.

PO3

Students should be able to demonstrate a degree of mastery over the area as per the specialization of the program. The mastery should be at a level higher than the requirements in the appropriate bachelor program

Program Specific Outcomes (PSOs)

PSO1

Ability to analyze, design, implement, and test software systems based on requirement specifications and development methodologies of software systems.

PSO2

Apply computer science theory blended with engineering mathematics to solve computational tasks and model real world problems using appropriate programming language, data structure, and algorithms.

PSO3

Ability to explore technological advancements in various domains, evaluate its merits and identify research gaps to provide solution to new ideas and innovations.

Career Prospects

With the increasing demand for highly qualified researchers, academicians, and innovation leaders in the computing and technology domains, Ph.D. graduates in Computer Science & Engineering can pursue a wide range of advanced research, academic, and strategic leadership roles across universities, research organizations, global technology industries, government agencies, and innovation-driven enterprises. The doctoral program equips scholars with deep domain expertise, independent research capability, and problem-solving skills required for high-impact roles.Ph.D. graduates may pursue the following opportunities:

They have various career opportunities as:
  • Research Scientist / Senior Research Scientist (AI / ML / Data Science / Cyber Security)
  • Principal Investigator / Lead Researcher
  • Post-Doctoral Researcher
  • Chief Scientist / Research & Development Head
  • Professor / Associate Professor / Assistant Professor
  • AI Architect / Machine Learning Architect
  • Data Science Research Lead
  • Computer Vision Research Engineer
  • Cyber Security Researcher / Security Architect
  • Blockchain Researcher / Distributed Systems Expert
  • High-Performance Computing (HPC) Research Engineer
  • Systems Architect / Software Architect
  • Technology Consultant / Research Consultant
  • Innovation Manager / Product Research Lead
  • Entrepreneur / Start-up Founder (Deep Tech, AI, Data-driven Solutions)
  • Policy Advisor / Technical Expert (Government & Research Bodies)
Graphic Era (Deemed to be University)

Placements

Graphic Era Deemed to be University has a strong connection to various industries, and its track record for successfully placing students in reputable positions is outstanding, with graduates being placed in internships and permanent roles. The university has formed valuable relationships with globally recognized companies such as Amazon, Microsoft, Google, Walmart, Adobe, and many more, providing students with ample opportunities to kick-start their careers.

Graduates from Graphic Era Deemed to be University can be confident in their ability to succeed in the workforce due to the exceptional training and real-world experience they gain from their internships and placements with these top-tier companies.

Notes: Semester 1 and 2 are applicable only for regular entry students. Lateral entry students begin from Semester 3.

Course Curriculum

  • Research Methodology and IPR
  • Mobile Computing
  • Advanced Operating Systems
  • Networking Protocols
  • Data Warehousing and Mining
  • Cloud Computing
  • Internet of Things
  • Algorithm Design and Techniques
  • Wireless Sensor Networks
  • Applied Data Science
  • Applied Cyber Security
  • Applied AI using Python
  • Machine Learning
  • Computer Vision and its Applications
  • Distributed Computing
  • Artificial Intelligence & Expert Systems

Frequently Asked Questions

Candidates with a valid UGC-NET (Category 1, 2 or 3) or GATE score are exempted from the written test. However, they must attend the online interview.

  • Mode :  Online
  • Type : MCQ
  • Sections : 50% Research Methodology + 50% Subject-Specific (as per GATE/UGC-NET syllabus)
  • Qualifying marks : 50%
  • Interview : Same day (online), where candidates discuss their research interests.

Yes. Final-semester candidates can apply, but admission will be provisional until submission of final results.

Yes. The University offers: Rs. 36,000/month (for UGC-NET Category 1) Up to Rs. 32,000/month (for UGC-NET Category 2 & 3 or GEU Entrance Top Rankers) Meritorious Scholars’ Research Grant up to Rs. 2,00,000 per year Merit-cum-means tuition fee waivers

Scholars have access to:

  • Advanced laboratories & research centres
  • Technology Business Incubator support
  • Publication & patent guidance
  • International workshops and conferences
  • Experienced supervisors and interdisciplinary research culture

Yes. Part-Time applicants must submit a No Objection Certificate (NOC) from their employer.

Yes. Fee structure varies for Full-Time and Part-Time candidates.

All information—exam link, schedule, and interview details—will be sent to the registered mobile number and email.

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