Institute of High Performance Computing

Successful candidates will join a number of exciting research projects on studies of thin films, nanocrystalline materials, self-assembly of nanoscale materials, and hierarchical and multifunctional materials. They will also have the opportunity to work at Brown University as visiting scholars for an extended period according to research needs.

• A PhD in Mechanics, Materials Science, Physics or its equivalent
• Demonstrated ability to conduct scholarly research, as evidenced by a thesis or publications in top-tier international journals
• Able to make clear and effective oral and written presentations of scientific and technical information.
• Candidates with expertise in theoretical work, and modeling and computation of mechanical behaviors and properties of materials, are strongly encouraged to apply

You will be engaged in epidemiological analysis and modelling research. Your primary task will be the manipulation and analysis of datasets relating to infectious diseases (e.g. spatio-temporal and/or data mining methods. Your scope will also include corresponding with related parties, evaluation and interpretation of findings, reporting/presentation of study results and assisting/supervising database development.

·        A PhD in Epidemiology, Statistics or its equivalent; or Masters of Public Health, Statistics or Epidemiology with 3 to 5 years experience in statistical/data analysis/machine learning.

·        Previous work on weather modelling/analysis will be an advantage

·        Knowledge of a wide variety of statistical procedures applied to public health data would be advantageous including but not limited to multivariate correlation analysis, time series analysis, categorical data analysis, logistic regression, survival analysis, spatial analysis, exploratory and graphical methods.

You will be engaged in research and development using advanced data mining techniques and algorithms to handle large databsets comprising spatial-temporal information. Projects span climate modeling, infectious disease and large data analysis.
Fresh graduates with passion to explore on utilizing HPC topics for large data mining problem are also encouraged to apply

• A PhD or Master"s Degree in Computer Science/Statistics/Mathematics, specialising in epidermiology modeling and weather prediction
• Relevant working experience in C/C++, MATLAB, SQL, Java, Windows or Unix programming, with preference given to those with strong background in Mathematics/ Statistics
• Strong conceptual understanding of a range of current data mining technologies (including but not limited to spatial-temporal/distributed data mining and machine learning applications, incremental learning, informatics visualisation etc.
• Experience in data management and warehousing techniques would be an advantage

You will be exploring new paradigms in system level tools and programming framework for heterogeneous HPC architectures.  You should be self-motivated and capable of performing independent research. You will be required to define and drive new research thrusts and to mentor young researchers.

Relevant areas of research include but are not limited to:

1.new software engineering process/practice for emerging hybrid computing clusters;
2.compiler and scheduling techniques for hybrid platform consisting of multicores and accelerators
3.parallelization and performance optimization on emerging architectures

•A PhD/MSc in Computer Science, Mathematics or its equivalent with proven ability to perform independent research;

•Good knowledge in at least 2 of the following areas: compiler, scheduling, operating system, parallel numerical techniques and algorithm optimization
 
•Candidates with hands-on experience in scientific and computer-intensive applications cum in-depth exposure to emerging architecture are preferred
 

You will predict, explore and understand the fundamental properties and structure of materials as well as develop new materials using novel computational approaches such as molecular dynamics, ab initio and multiscale methods. You will have access to state-of-the-art computing facilities and tools to study a wide range of challenging problems from green energy to electronics.

• A PhD in Physics/ Chemistry/ Mathematics/ Material Science or its equivalent
• Strong interest and experience in modelling and simulation work

You should possess the ability to combine different techniques for multiscale modeling of materials. These techniques are based on first-principles (density-functional based) theory, tight-binding methods, force-field methods (include coarse grained potentials), phase-field methods, and hand-shake algorithms (or other novel algorithms) to enable multiscale modeling of materials. The combined techniques will be used to perform large-scale simulations of materials such as metals and semiconductors involving point, line, and 2D defects.

• A PhD in Physics/ Chemistry/ Materials Science or its equivalent
• Working experience in Fortran90, C, Linux environment is essential. Those with good knowledge in MPI techniques for parallelization will have an advantage

We wish to invite applicants with a passion and interest in solving challenging scientific and engineering problems using computational science and engineering technologies to join us in one of the following areas :

• Chemistry/Materials Science
• Computer Science/IT
• Electronics
• Environmental Modelling
• Fluid Dynamics
• Photonics
• Structural Mechanics 

• At least a 2nd class Upper Honours Degree in Science or Engineering
• Good knowledge of programming skills such as Matlab, Fortran, C/C++, Java
• A self-motivated team player with good communication and interpersonal skills 

You will use Computational Fluid Dynamics (CFD) tools to investigate climatic impacts on building thermal loadings, public health and flora.

- Bachelor"s Degree in Engineering, Applied Mathematics or Science

- Knowledge in fluid dynamics and preferably some experience in computational fluid dynamics (CFD) modelling 

- Knowledge of commercial CFD software e.g. FLUENT and user-defined function (UDF) programming in C/C++

You will be engaged in the development of tools/application. The main focus is to provide the means to extract, process, load and deliver large dataset to the researcher in a secure and timely manner.

- At least a Bachelor"s Degree with 2nd upper honours in Computer Science or Engineering

- Knowledge of data intergration/fusion and working experience with various databases e.g. Oracle, Mysql

- GIS knowledge and strong programming skills (such as Fortran, C etc) would be an advantage

- Knowledge in writing parser and/or ETL/BI tools, unix/windows scripting and basic system administration

- Web development experience preferable with knowledge on Web Oriented Architecture e.g REST, JSON 

You will be engaged in research and development in epidemiological analysis and modelling. You will manipulate and analyse large datasets comprising spatial-temporal information relating to infectious disease and to determine their correlations. You will conduct studies of environmental change and the impacts affecting public health; this will include conducting correspondences related to the work, evaluation and interpretation of the findings, and reporting/presentation of study results. You will assist and/or supervise database development and perform statistical analysis on data collected from research studies

- At least a Bachelor’s Degree with 2^nd Upper Honours in Epidemiology, Statistics, Science or Engineering

-   Knowledge of a wide variety of statistical procedures applied to public health data wouldbe advantageous including but not limited to multivariate correlation analysis, time seriesanalysis, categorical data analysis, logistic regression, survival analysis, spatial analysis,exploratory and graphical methods.