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PHD-SIG in Data Science at Symbiosis International University (SIU)
Pune, Maharashtra
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About the Specialization
What is Data Science at Symbiosis International University (SIU) Pune?
This Data Science PhD program at Symbiosis International University, under the Symbiosis Institute of Geoinformatics (SIG), focuses on advanced research at the intersection of data science and geospatial technologies. It delves into leveraging vast datasets, artificial intelligence, and machine learning techniques to derive actionable insights from complex geographical information, addressing critical real-world challenges in India.
Who Should Apply?
This program is ideal for master''''s degree holders in Computer Science, Information Technology, Geoinformatics, Statistics, or related fields who possess a strong analytical aptitude and a passion for research. It targets individuals aspiring to contribute original knowledge, develop innovative data-driven solutions, and pursue academic or high-level research careers within the geospatial and data science domains.
Why Choose This Course?
Graduates of this program can expect to secure leading research and development roles in government organizations like ISRO, NRSA, private geospatial analytics firms, or become faculty members in academia across India. They will be equipped to develop cutting-edge algorithms and models for complex data challenges, with potential starting salaries ranging from INR 10-25 LPA depending on the sector and experience.
Student Success Practices
Foundation Stage
Master Research Methodology and Foundational Data Science- (Coursework Phase (typically first 1-2 semesters))
Thoroughly engage with the Research Methodology coursework, focusing on critical thinking, ethical considerations, and statistical rigor. Simultaneously, strengthen fundamental data science skills in programming (Python/R), linear algebra, and probability, which are crucial for advanced research.
Tools & Resources
NPTEL courses on Research Methodology and Statistics, Coursera/edX for advanced Python/R programming in Data Science, Scopus/Web of Science for literature search
Career Connection
A solid foundation is essential for defining a robust research problem and executing it effectively, directly impacting the quality of your thesis and future research credibility.
Build Comprehensive Literature Review Skills- (Coursework Phase (typically first 1-2 semesters))
Dedicate significant time to systematically reviewing existing literature in your chosen area of Data Science and Geoinformatics. Learn to identify research gaps, critically analyze methodologies, and synthesize findings to establish the relevance and novelty of your proposed research.
Tools & Resources
Mendeley/Zotero for reference management, Google Scholar, IEEE Xplore, ACM Digital Library for publications, SIU Library resources
Career Connection
Proficiency in literature review underpins successful research proposals and publications, positioning you as an expert in your domain for academic and industry R&D roles.
Develop Advanced Programming and Data Manipulation Skills- (Coursework Phase and early Research Phase)
Focus on developing high-proficiency in programming languages like Python (with libraries like NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch) and R. Gain expertise in handling large datasets, especially geospatial data, using libraries like GeoPandas, GDAL/OGR, and processing tools.
Tools & Resources
Kaggle, HackerRank for coding practice, GitHub for version control and project showcasing, QGIS/ArcGIS for geospatial data handling
Career Connection
Strong technical skills are indispensable for implementing research methodologies, running experiments, and will significantly enhance your employability in data scientist and research engineer roles.
Intermediate Stage
Formulate a Novel Research Problem and Proposal- (After coursework, typically Year 1-2)
Collaborate closely with your research guide to define a clear, impactful, and feasible research problem within Data Science and Geoinformatics. Develop a comprehensive research proposal outlining objectives, methodology, expected outcomes, and a detailed timeline for your doctoral work.
Tools & Resources
Regular meetings with Research Advisory Committee (RAC), SIU research proposal guidelines, Feedback from peers and mentors
Career Connection
A well-articulated research problem is the cornerstone of a successful PhD, directly influencing your ability to produce high-impact publications and secure grants.
Engage in Research Seminars and Presentations- (Year 2-3)
Actively participate in departmental seminars, workshops, and conferences (national/international) to present your preliminary research findings. Seek constructive feedback, network with fellow researchers, and refine your presentation and communication skills.
Tools & Resources
SIU research colloquiums, National/International Data Science/GIS conferences (e.g., GeoSmart India, IEEE conferences), Presentation software like LaTeX Beamer
Career Connection
Presenting your work enhances visibility, fosters collaborations, and prepares you for academic and public speaking roles, which are vital for career progression.
Cultivate Expertise in Specialized Data Science Techniques for Geospatial Applications- (Year 2-4)
Deep dive into advanced topics relevant to your research, such as spatial machine learning, time-series analysis of satellite imagery, explainable AI in remote sensing, or big data architectures for real-time geospatial processing. This involves independent learning, online courses, and specialized workshops.
Tools & Resources
Deep Learning Specialization (Coursera), TensorFlow/PyTorch documentation, Online forums like Stack Overflow, GIS Stack Exchange, Access to SIU computing clusters
Career Connection
Developing specialized expertise makes you a highly sought-after professional in specific niches of the data science and geospatial industry, opening doors to advanced research roles.
Advanced Stage
Focus on High-Quality Research Publications- (Year 3-5)
Prioritize publishing your research findings in peer-reviewed journals of high repute (Scopus/WoS indexed, Q1/Q2 journals). Aim for at least 2-3 quality publications before thesis submission, ensuring adherence to academic integrity and publication ethics.
Tools & Resources
Journal submission platforms, Academic writing workshops, Grammarly/Turnitin for proofreading and plagiarism checks
Career Connection
Publications are the primary currency in academia and significantly boost your profile for post-doctoral positions, faculty roles, and R&D jobs in leading companies.
Network and Collaborate Extensively- (Year 4-6)
Actively build a professional network by connecting with leading researchers, industry experts, and potential employers at conferences, workshops, and online platforms. Explore collaboration opportunities for joint projects or co-authorships.
Tools & Resources
LinkedIn, ResearchGate, Conference proceedings and delegate lists, SIU alumni network
Career Connection
Networking is crucial for career opportunities, mentorship, and staying updated with industry trends, often leading directly to placements or impactful collaborations.
Prepare for Thesis Defense and Career Transition- (Final Year (Year 4-6))
Systematically compile, write, and refine your doctoral thesis, ensuring it presents original research and adheres to SIU''''s guidelines. Simultaneously, prepare for the viva voce examination and begin planning your post-PhD career path, whether in academia, industry R&D, or entrepreneurship.
Tools & Resources
SIU Thesis Writing Guidelines, Mock viva sessions with peers/mentors, Career services at SIU for resume building and interview preparation
Career Connection
A successful thesis defense is the culmination of your PhD journey. Proactive career planning ensures a smooth transition into your desired professional role, leveraging your advanced research capabilities.
Program Structure and Curriculum
Eligibility:
- Master’s Degree or a professional degree declared equivalent to the Master’s Degree by the corresponding statutory regulatory body, with at least 55% marks in aggregate or its equivalent grade ''''B'''' in the UGC 7-point scale (or an equivalent grading system). A relaxation of 5% of marks (or equivalent grade) is allowed for candidates belonging to SC/ST/OBC (non-creamy layer)/Differently-abled categories.
Duration: Minimum 3 years, Maximum 6 years (full-time)
Credits: 12-16 credits (for coursework phase) Credits
Assessment: Internal: Varies by course (50% for Research Methodology, 100% for Review of Literature & Seminar and Specialized Courses), External: Varies by course (50% for Research Methodology, Not applicable for Review of Literature & Seminar and Specialized Courses)
