Admission


We look for students with excellent academic standing, who are highly accomplished and self-motivated students. Successful candidates are supported for their tuition and living expenses by the CSE. For those who show high performance, the chance of oversea research training will also be provided. Students applying to our programs should have earned a bachelor's or master's degree in a science, mathematics, computer science or engineering and possess a keen interest in computational science.

  • Applicants in engineering - Should have taken Engineering Mathematics or equivalent courses (Linear Algebra, Differential Equation, Calculus, etc.).
  • Applicants in mathematics - Should have taken Advanced Calculus, Linear Algebra and Real Analysis.
  • Applicants in science - Should have taken Advanced Calculus or equivalent courses (Linear Algebra, Differential Equation, Calculus, etc.).

CSE Degree achievement (계산과학공학과 학위과정)

  • Ph.D/MS CSE-Mathematics
  • Ph.D/MS CSE-Mechanical/Electrical Eng.

CSE try to provide multidisciplinary areas combining the traditional fields of engineering - electrical, mechanical, biomedical, and material sciences. Our programs focus on modeling-computer simulation-visualization, based on applied mathematics.


Specific Medical Imaging (MI) research areas include :

Medical imaging

  • Reconstruction algorithm for Magnetic Resonance Electrical Impedance Tomography (MREIT), Electrical Impedance Tomography (EIT)
  • Numerical tools for Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Ultrasound Systems

Applied partial differential equations, harmonic analyis

  • Mathematical modeling and analysis for inverse problems

Biomedical image processing

  • Denoising, deblurring, segmentation and enhancement in various biomedical images

MI Team Requirements

  • BS or MS degree in applied mathematics, physics or engineering
  • Good knowledge of scientific computation, image processing or computational fluid dynamics
  • Good programming skills: Matlab, Fortran or C++
  • Good command of written and spoken English.

Specific Computational Fluid Dynamics (CFD) research areas include:

  • Direct numerical simulation/Large eddy simulation of particle-laden turbulence physics
  • Direct numerical simulation of flow around finite-sized particles (or droplets) emphasizing cloud formation; immersed boundary methods, and level-set methods
  • Simulations of complex flows;
  • Large eddy simulation of pollutant dispersion in urban street canyons
  • Hybrid incompressible/compressible simulation of cloud dispersion after a nuclear explosion
  • Contaminant transport in indoor environments due to transient events (human walking, door motion)
  • Large eddy simulation of atmospheric wind-turbine array boundary layers
  • Simulations of micro or nano-fluid phenomena using the Lattice Boltzmann Method

CFD Team Requirements

  • BS or MS degree in applied mathematics, physics or engineering
  • Good knowledge of scientific computation, image processing or computational fluid dynamics
  • Good programming skills: Matlab, Fortran or C++
  • Good command of written and spoken English.

Specific Numerical Analysis (NA) research areas include:

  • Theory of partial differential equations
  • Numerical analysis and scientific computing
  • Design and mathematical analysis of computational algorithms for mathematical models in science and engineering
  • Mathematical biology

NA Team Requirements

  • BS or MS degree in applied mathematics, physics or engineering
  • Good knowledge of scientific computation, image processing or computational fluid dynamics
  • Good programming skills: Matlab, Fortran or C++
  • Good command of written and spoken English.

Scholarships

  1. We look for students with excellent academic trackrecords who are highly accomplished and self-motivated. Excellent applicants will receive support for tuition and living expenses.
  2. Full scholarships include tuition, stipend, and health insurance. The amount of the annual stipend depends on prior academic experience and the length of your program (up to 4 years for Ph.D. students).