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PHD in Decision Science And Information Systems Dsis at Indian Institute of Management Nagpur
Nagpur, Maharashtra
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About the Specialization
What is Decision Science and Information Systems (DSIS) at Indian Institute of Management Nagpur Nagpur?
This Decision Science and Information Systems (DSIS) program at IIM Nagpur develops rigorous researchers and academicians. It addresses complex business problems using data-driven insights and technology. Integrating quantitative methods, analytical modeling, and IT applications, it is crucial for innovation and strategic decision-making in India. The program emphasizes theoretical depth and practical relevance for the evolving Indian industry.
Who Should Apply?
This program is ideal for aspiring scholars, academics, and research professionals with strong analytical skills in decision sciences or information systems. Candidates typically hold a Master''''s degree in a quantitative discipline, engineering, or management, seeking to contribute to academic knowledge or drive innovation in data-intensive Indian industries. It benefits professionals aiming for research or academic roles.
Why Choose This Course?
Graduates can pursue careers as faculty in top business schools or as research scientists/consultants in leading Indian and multinational corporations. They will conduct independent research, publish in esteemed journals, and significantly contribute to knowledge. The program develops critical thinking and problem-solving skills, highly valued in India''''s booming digital economy and data science domains.
Student Success Practices
Foundation Stage
Master Research Fundamentals- (Year 1)
Diligently focus on building a strong foundation in quantitative and qualitative research methodologies, econometrics, and data analytics. Attend all core lectures, participate in discussions, and actively engage with foundational texts to grasp core concepts thoroughly.
Tools & Resources
IIM Nagpur Library databases (JSTOR, Scopus), R/Python for statistical computing, Online courses on Coursera/edX for brushing up basics
Career Connection
A robust methodological understanding is critical for all future research, enabling the design of rigorous studies and enhancing credibility in academic and industry research roles.
Engage with Faculty Mentors- (Year 1)
Proactively seek interactions with faculty members in the DSIS area and beyond. Discuss research interests, seek guidance on foundational course topics, and explore potential areas for future specialization. Attend faculty research presentations and seminars.
Tools & Resources
Faculty office hours, Departmental seminars, IIM Nagpur research colloquiums
Career Connection
Building strong faculty relationships can lead to early research collaborations, mentorship for thesis work, and valuable networking opportunities for academic placements.
Develop Academic Reading Habits- (Year 1)
Cultivate a habit of reading academic papers regularly, starting with seminal works in Decision Science and Information Systems. Focus on understanding research questions, methodologies, and contributions. Begin synthesizing information and identifying gaps in existing literature.
Tools & Resources
Google Scholar, Specific journal databases (e.g., MIS Quarterly, Operations Research), Reference management software (Mendeley, Zotero)
Career Connection
This practice is fundamental for identifying viable research problems, staying updated with advancements, and ultimately contributing to scholarly discourse, essential for publishing and academic success.
Intermediate Stage
Deep Dive into Specialization- (Year 2)
Intensively focus on area-specific courses, engaging deeply with advanced topics in Decision Science and Information Systems. Explore diverse sub-fields within DSIS and identify a potential research niche. Actively participate in advanced seminars and research groups.
Tools & Resources
Specialized academic journals, IIM Nagpur DSIS department workshops, Faculty-led research groups
Career Connection
This deep immersion helps in formulating a precise research problem for the doctoral thesis and positions the scholar as an expert in their chosen domain, making them attractive to academic and specialized industry roles.
Prepare for Comprehensive Exam- (End of Year 2)
Systematically review all coursework material, both foundation and area-specific, in preparation for the comprehensive examination. Form study groups with peers, practice answering theoretical and applied questions, and seek clarification from faculty.
Tools & Resources
Course notes, Textbooks, Past exam papers (if available), Peer study groups
Career Connection
Passing the comprehensive exam is a critical milestone for PhD candidates, signifying readiness to embark on independent research and progression towards doctoral candidacy, a prerequisite for most academic jobs.
Explore Research Software & Tools- (Year 2)
Gain proficiency in advanced statistical, optimization, or simulation software relevant to DSIS research. This might include specialized packages in R/Python, simulation tools like Arena, or optimization solvers. Apply these tools to mini-projects or assignments.
Tools & Resources
RStudio, Python with libraries (SciPy, scikit-learn, TensorFlow, PyTorch), Gurobi/CPLEX, Specialized data analytics platforms
Career Connection
Technical proficiency in research tools is highly valued in both academic research and advanced analytics roles in industry, enabling efficient data analysis and model building for complex problems.
Advanced Stage
Develop and Defend Thesis Proposal- (Year 3)
Work closely with the thesis supervisor to refine the research question, develop a robust methodology, and articulate the expected contributions of the thesis. Prepare and successfully defend the thesis proposal to the doctoral advisory committee.
Tools & Resources
Thesis supervisor guidance, Doctoral committee feedback, Literature review databases, Research proposal writing workshops
Career Connection
A well-defined and defended thesis proposal is the gateway to independent doctoral research, laying the groundwork for a significant academic contribution and enabling entry into the research phase crucial for career advancement.
Engage in Conference Presentations & Publishing- (Years 3-5)
Actively write research papers based on ongoing thesis work and submit them to reputable academic conferences (e.g., POMS, INFORMS, AMCIS for DSIS). Present findings to receive feedback and build an academic network. Aim for publications in peer-reviewed journals.
Tools & Resources
Academic writing support, Conference submission platforms, Journal databases, Faculty co-authorship
Career Connection
Presenting at conferences and publishing in journals are vital for establishing a research profile, gaining visibility in the academic community, and are primary metrics for faculty hiring and promotion.
Prepare for Academic Job Market- (Years 4-5 onwards)
Systematically prepare for the academic job market, which includes developing a strong CV, teaching philosophy statement, research statement, and preparing for job talks. Network with potential employers at conferences and through academic contacts. Practice mock interviews and job talks.
Tools & Resources
Career services, Faculty mentors, Academic job market websites (e.g., INFORMS Job Ads, AOM, specific university job portals), Mock interview panels
Career Connection
Focused preparation ensures candidates are competitive for faculty positions in top-tier institutions, aligning their research and teaching profiles with institutional needs and securing their desired career trajectory.
Program Structure and Curriculum
Eligibility:
- Master’s Degree or 2-year Post Graduate Diploma in any discipline with at least 55% marks (or equivalent GPA); OR Professional qualifications like CA, CS, CMA (with a minimum of 55% aggregate marks) along with a Bachelor''''s degree (10+2+3 scheme); OR 4-year / 8-semester Bachelor’s degree with Research (B.E./B.Tech./B.Arch. etc.) with a minimum of 65% marks (or equivalent GPA). Valid scores in CAT, GRE, GMAT, GATE, or JRF (UGC/CSIR) for the last 5 years. Age: Not more than 55 years as on June 1, 2024.
Duration: 5-7 years
Credits: Minimum 48 credits (for coursework) Credits
Assessment: Assessment pattern not specified
