MINIMUM ADMISSION REQUIREMENTS FOR PHD IN INDIA

• To apply for the Phd,you must normally have a MTech/ME in any Branch of Engineering
• Must also have a valid GATE score
• Some Universities may ask First Class Marks in the previous Academic Performance.
• In certain cases,if a Student is one of the Topper in an Good Universitty with above 75% maks in Bachelours Degree ie BTech/BE is eligible to do Phd in some Universities.
• Under Quality Improvement Program students may differ requirements for Admission.For example caste,disabilty etc...

MINIMUM ADMISSION REQUIREMENTS FOR PHD IN USA

• minimum 3.5 GPA(previous degree performance).
• acceptable score on the GRE
• minimum TOEFL score of 580 on the written exam or 237 on the computer-based exam for international applicants whose native language is not English and who do not have a prior degree from an accredited U.S. institution
• three letters of recommendation form previuos university.
• some universites may ask students to produce research proposal on ur topic.              

            An overall evaluation of your credentials will be used as a basis for admission.

many more research areas in computer science

          

•  computer security
• Uses of randomness in complexity theory and algorithms
•  Efficient algorithms for finding approximate solutions to NP-hard problems (or proving that they don't exist)
• Cryptography.
• Computer Architecture 
• Cryptography, Complexity Theory, Randomness and Computation.
• machine learning,graphical models,computational statistics,information retrieval,natural language processing
• Design and analysis of algorithms, particularly approximation algorithms, on-line algorithms and efficient algorithms for dealing with large volumes of data.
• Computational Geometry, Sublinear Algorithms, Clustering, Discrepancy Theory, Lower Bounds
• Computer architecture and organization; 
• architecturally-focused performance analysis.
• Computer Music; 
• Simulation of Musical Acoustics and Voice;
•  Real-Time Expressive Computer Control, Human-Computer Interfacing.
• Visualization, pervasive computing, software engineering
• Computer security; 
• network software;
•  technology law and policy.
• computer graphics, animation.
•  operating systems, distributed systems, computer networks, programming languages, computer architecture. 
•  Distributed systems, security, networking, applied cryptography 
• Structural bioinformatics and computer graphics.
• Networked Systems, Operating Systems, Hardware/Software Interfaces
• application-specific languages, document preparation, user interfaces, software tools, programming methodology 
•  Search and retrieval of information;
•  data mining, particularly clustering; 
• combinatorial algorithms
• Computer vision, human vision, machine learning.
•  Parallel architectures and systems; 
• distributed systems; 
• operating systems.
• Network/Web servers, operating systems, high-performance applications.
• Networked systems, communication protocols, operating systems. 
• : Data networks, network measurement, network management, routing protocols, network troubleshooting.
•  computer graphics; acquisition of 3D shape, reflectance, and appearance of real-world objects
•  Machine learning
• Finding efficient algorithms for fundamental practical problems by studying algorithms at all levels through the design-analysis-implementation cycle;
•  dynamic graphical simulations of algorithms in operation.
• Parallel computing systems and applications: 
• parallel applications and their implications for software and architectural design; 
• system software and programming environments for multiprocessors. Special interest in applications of computing in computational biology, especially protein structure determination and simulating the immune system
• computational molecular biology, as well as its interface with machine learning and algorithms. 
• auctions, agent-based simulation, soliton computing. 
• Data structures; 
• graph algorithms
•  combinatorial optimization; 
• computational complexity;
•  computational geometry;
•  parallel algorithms. 
•  Bioinformatics;
•  analysis of large-scale biological data sets (genomics, gene expression, proteomics, biological networks); 
• algorithms for integration of data from multiple data sources; 
• visualization of biological data;
•  machine learning methods in bioinformatics.
• Programming languages, type systems, compilers, data processing and security. 
• design, analysis, and implementation of algorithms;
•  combinatorial optimization; 
• graphs and networks.
•  computational approaches to analysis of large-scale genomics data sets 

VARIETY OF COURSES AND RESEARCH AREAS IN COMPUTER SCIENCE

Choose from a variety of courses and research areas:

• algorithm analysis
• architecture
• artificial intelligence
• computer security
• computer systems
• database systems
• distributed computing
• game programming
• image processing
• networking
• numerical analysis
• operating systems
• pattern recognition
• programming languages
• simulation and modeling

share ideas on research

hi my friends......iam just now completed my MSC IN COMPUTER SCIENCE in london university...i would like to do phd in operating systems or programming languages....can u give some best tobics in computer science and some advices to me....i dont know any thing just now i completed my msc...but if u give some ideas i can do......................