About Program

Overview

This program provides training in applied mathematics techniques and focusing on mathematical models of real- world processes, their formulation in terms of differential equations and methods solution - both numerical and analytical. Mathematical modelling is a valuable skill for solving the real problems and challenges faced by different sectors and provide a useful language to describe, solve, and validate the problem.

Central to the course will be practical problems that arise in industrial applications, information technology, energy, drug development, DNA mapping, and environmental research.

Goals

The main objectives of the program are to:

Understand the theory of partial differential equations, numerical discretization, error analysis.
Understand the principles of continuous and discrete optimization, variation calculations, game theory.
Demonstrate the theory of control, infinite on infinite dimension, optimal control, inverse problems.
Analyze, simulation and modelling tools used in life sciences.
Understand the principles of scientific computing, parallel computing, and computer-aided design.
Knowledge in various application of mathematical modelling in the biology, computer science, mechanics, medicine, and environmental sector.

Career of Graduates

Mathematical Modelling and Computation is an extremely popular program. Successful students will be well placed to satisfy the growing demand for mathematical modelling in industry, medicine, and environment, and will learn and practice the skills necessary to pursue farther research.

Student can find suitable job wherever it is necessary to use mathematical models and where models are used to obtain information about behavior in reality. Thus student might be a valuable member of research and development teams for example in the area of managing and modelling complex processes.

Program Learning Outcomes

Upon completion of this program, students should be equipped with comprehensive knowledge, skills, and abilities to excel in their endeavors.

Understand the principles and methods of the formulation and analysis of mathematical models of systems and processes in engineering and the natural science.

Acquire knowledge of dimensional analysis, scaling, perturbation analysis, dynamic models, and conversation laws.

Understand the possibilities for performing analytical and numerical computations based on the model.

Formulate and qualitatively analyze mathematical models of a wide range of systems and processes.

Work in cross – disciplinary groups, and is able to communicate the results orally and in writing.

Critically and systematically integrate knowledge in pure and applied mathematics and analyze and manipulate mathematical models.

Identify questions in pure mathematics and be able to build models.

Judgements with regards to relevant scientific and social perspectives for mathematical modelling in economics and IT.

Address experimental, computational and use of mathematical models particularly in the fields described.

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