The Doctor of Philosophy (PhD) Program aims to cultivate doctoral graduates who are capable of the design, initiation and execution of original research, who can independently conduct advanced research projects, who possess both a broad knowledge of modern life science and an in-depth knowledge of specialized areas, and who can also contribute original knowledge to the field of life sciences by publishing their findings in peer-reviewed international journals.

Scientific Computation Concentration

Scientific computation is among the fastest-growing multidisciplinary research area and it serves as a bridge between the traditional domains of theoretical and experimental sciences. Computation research covers many areas in science and engineering. The multidisciplinary nature of computational science and its wide-ranging scope means that its training and research can best be integrated into different disciplines to equip students with a solid foundation of the knowledge in focused areas. This concentration is intended for research postgraduate students who are interested in pursuing research in computation related research. Students can enroll in a particular discipline for research with a special focus in Scientific Computation.

The Scientific Computation Concentration is open to research postgraduates in the School of Science and the School of Engineering.

RESEARCH FOCI

The Scientific Computation Concentration is designed to equip students with a solid foundation of the knowledge in different disciplines with following research foci.

Computational Biology and Bioinformatics

• Computational structural biology
• Bioinformatics
• Computational neuroscience models of multi-sensory integration and motion sickness

Computational Fluid Dynamics and Soft-Matter Simulation

• Multi-scale phenomena at fluid-solid interfaces
• Kinetic methods for continuum and near-continuum flows
• Multi-scale coupled circulation-ecosystem simulation in the ocean
• Supersonic convection and radiation-convection transition in astrophysics
• Large-scale flow structures and their effects in turbulent thermal convection
• Phase transitions in colloids

Computational Material Science

• Discovery and design of wave-functional meta-materials and photonic crystals
• Catalyst design
• First principles and phenomenological modeling of nanomaterial
• Spin dynamics in nanostructures
• Dislocation dynamics

Efficient High-performance Computing Systems

• Energy and cost efficient computing systems
• Merged scale-up and scale-out computing systems for HPCs and data centers

Environmental and Atmospheric Modeling

• Real-time air quality analysis
• Development of an operational air quality prediction system
• Numerical investigation of air pollutant inception: the role of humidity
• Collisions and diffusion of water clusters on hydrophilic and hydrophobic surfaces for chip/device cooling
• Multiscale simulation of thermal conductivity of nanomaterials for thermal management

High Performance Computing and Data Analysis

• High-performance deep learning
• Big data analytics

Information Statistical Physics and Big Data Analysis on Networks

• Stability, reliability and robustness of power grids
• Social network: dynamics of opinion formation and community detection
• Random walk and games
• Analysis of big data using evolution computation and quantum genetic algorithm
• Agent dynamics and artificial life in econophysics