MS Mathematics

MS in Mathematics aims to provide a thorough background in theory, quantitative methods and applications commensurate with international standards, offering the opportunity of more specialized training in selected areas of pure and applied mathematics. (DRC is short for Departmental Research Committee)


ELIGIBILITY:

In order to be eligible to apply for admission in MS in Mathematics a candidate should:

a) Possesses a BS / MSc (16 year education) degree from a recognized university in Mathematics.
b) Have passed the last examination with at least 60% marks (or CGPA 2.5 whatever applies)
c) Experience is not mandatory for admission to MS Mathematics program


ADMISSION PROCESS:

All eligible candidates would be required to:

a) Sit and qualify an admission test (equivalent to GRE subjective-Mathematics/ GAT subjective-Mathematics of NTS) and if successful, appear in an interview / presentation before a selection panel.
b) Candidates who have a minimum 50 percentile score in GRE (International) subjective Mathematics are exempted from the IBA admission test, BUT not from the interview.


DURATION:

MS: 2 - 4 years.


FINANCIAL ASSISTANCE:

MS students can opt for full time student status for financial support which is provided in the form of assisting duties for teaching and research. This support is up to a maximum of Rs. 30,000 per month. This facility is only extended to those students who maintain a cumulative GPA of 3.00, and register in 4 courses each semester in the MS Mathematics program. In addition to this, the students availing financial support must NOT work elsewhere. The maximum duration of financial assistance (in which student is considered as a full-time student) is two years, it can be extended for one more year on the recommendation of supervisor and DRC.


PART TIME STUDENTS:

MS students can also join the program on a part-time basis (i.e. those students who are not offered (or do not willfully avail / opt-for financial assistance), with a condition that they cannot register in more than 2 courses in a semester.


REQUIREMENTS FOR THE AWARD OF MS DEGREE:

For award of an MS in Mathematics a candidate should:
a) Complete 30 credit hours that include 24 credit hours (8 courses) of course work and 6 credit hours of thesis.
b) Six courses (mentioned in the list below) at 500 level are Core courses that every student must do.
c) In addition, a student has to do two electives to be chosen from the list given below at 500 level. A student can also choose a PhD mathematics course as an elective course, by the approval of the DRC.
d) The eligibility for doing an MS thesis is student acquiring a CGPA of 3.0.
e) Students who do not qualify the eligibility criterion for doing an MS thesis, will be required to do two additional courses (6 credit hours in addition) and graduate with an MS degree only. Such MS graduates would lose the eligibility of doing a PhD in future from IBA.
f) Public defense of the MS thesis and completion of the degree will be governed as per IBA policy.


CORE COURSES:

The Departmental Research Committee is authorized to introduce any new course added to the following list as and when required

First Semester:
MTS511 Advanced Real Analysis
MTS 513 Topics in Algebra
MTS 515 Advanced Numerical Analysis
MTS 516 Topology
Second Semester:
MTS 512 Measure Theory & Integration
MTS 514 Topics in Commutative Algebra
MTS 5XX Elective I
MTS 5XX Elective II


ELECTIVES COURSES:

The Departmental Research Committee is authorized to introduce any new course added to the following list as and when required.
MTS 521 Scientific Computing
MTS 525 Stochastic Processes II
MTS 529 Stochastic Differential Equations
MTS 533 Integral Equations
MTS 537 Mathematical Astronomy
MTS 539 Homological Algebra
MTS 541 Computational Algebraic Geometry
MTS 545 Applicable Modern Geometry I
MTS 549 Algebraic Geometry I
MTS 553 Algebraic Cycles I
MTS 557 Arithmetic Algebraic Geometry
MTS 561 Exploratory data Analysis
MTS 565 Mathematical Physics I
MTS 569 Statistical Data Mining & Knowledge Discovery
MTS 573 Statistical Machine Learning
MTS 577 Galois Theory
MTS581 Smooth Manifolds
MTS461 Nonlinear Dynamics and Chaos