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课程名称:利物浦大学数学科学硕士课程
课程类型:硕士课程-数学 / 统计 / 精算硕士
学校名称:利物浦大学 University of Liverpool
学校位置:西北地区
课程长度:12个月
开学日期:10月
 

介绍:

入学要求 Requirement:

学术要求:an Honours degree in Mathematics or with Mathematics as a major component (usually class 2:2 or better).

英语要求:IELTS 6.5 with minimum 5.5 in each component

学费 Tuition Fee: 2011/2012     £10,500

 
课程特征 Course Features:

The range of topics covered by the Mathematical Sciences MSc provides the breadth and depth required for advanced postgraduate study in the discipline.

Topics offered include:
•integral equations
•asymptotic theory of partial differential equations
•mathematical physics
•numerical methods
•theory of similarity and fractals
•mathematical biology
•optimal control theory
•number theory
•group theory
•algebraic geometry
•differential topology
•singularity theory
•knot theory
•dynamical systems
•statistics
•financial mathematics.

Successful completion of the first semester qualifies students for a Postgraduate Certificate, while successful completion of the first and second semesters will qualify you for a Postgraduate Diploma. Initial registration for either of these two awards is also possible.

 
课程内容 Course Content :

The programme has a modular structure with a total of 180 credits. In the first semester, there are three lectured modules (each 15 credits) and an instructional module in Maple and LaTeX (15 credits).

The second semester entails two lectured modules and a presentation module in which students prepare and deliver a seminar and write a mini dissertation (30 credits).

The programme finishes with a summer dissertation written under the supervision of a member of staff (60 credits).

Compulsory Modules
Maple and Latex
PreliminaryDissertation
Optional Modules
Chaos and Dynamical Systems
Further Methods of Applied Mathematics
Cartesian Tensors and Mathematical Models of Solids and Viscous Fluids
Quantum Mechanics
Population Dynamics
Introduction to Variational Calculus and Homogenization theory
Analysis and Number Theory
Number Theory
Group Theory
Applied Probability
Linear Statistical Models
Networks in Theory and Practice
Linear Differential Operators in Mathematical Physics*
Introduction to String Theory
Quantum Field Theory*
Curves and Singularities*
Representation Theory
Advanced Statistical Models
Applied Stochastic Models
Asymptotic Methods for Partial Differential Equations*
Quantitative Research Techniques*
Relativity
Introduction to Modern Particle Physics
Mathematical Economics
Combinatorics
Analytical Methods in Higher Geometry
Differential Geometry
Introduction to modern particle theory
Analytical and computational methods for Applied Mathematics
Mathematical Biology*
Waves .Mathematical Modelling*
Elliptic Curves
Galois Theory
Advanced Mathematical Methods
Reading Course•
Quantitative Methods for Research II
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