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.).
Please visit https://graduate.yonsei.ac.kr/graduate/index.do for more details about application requirements and procedures.
CSE Degree achievement (수학계산학부(계산과학공학) 학위과정)
- • Ph.D. in Computational Science and Engineering
- • M.S. in Computational Scinece and Enginnering
CSE tries to provide multidisciplinary areas combining the traditional fields of engineering - electrical, computer, 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.
Specific Data Science (DS) research areas include:
- • Data mining : Graph analysis engine and social network analysis, Healthcare informatics, Big data analytics and data warehouse, Neural network-based approach
- • Machine learning : Statistical signal processing, Clustering/classification/regression, Deep learning, Reinforcement learning
- • Wireless networking : Beyond 5G (or 6G) technology, Information-theoretic approach, Data-driven methodology and learning-based system design
DS Team Requirements
- • BS or MS degree in engineering, statistics, applied mathematics or physics
- • Good knowledge of fundamental mathematics in probability, statistics, and linear algebra
- • Good programming skills: Python, R 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).