国际学生入学条件
A Master's degree in Computer Science with a 78% average.
Three references, at least two academic
Proof of English language proficiency, if applicable. TOEFL 100 (writing 26, speaking 26), IELTS 7.5 (writing 7.0, speaking 7.0)
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雅思考试总分
7.5
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雅思考试指南
- 雅思总分:7.5
- 托福网考总分:100
- 托福笔试总分:160
- 其他语言考试:PTE (Academic) - 68 (writing 65, speaking 65)
CRICOS代码:
申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
SciCom小组对支持医学影像等领域应用的方法和软件进行了研究。
The David R. Cheriton School of Computer Science has an international reputation in teaching, academics, research, and employment. We attract exceptional students from all over the world to study and conduct research with our award-winning faculty. You can participate in research projects in a wide variety of topics with our internationally acclaimed researchers. Our research spans the field of computer science, from core work on systems, theory and programming languages to human-computer interaction, DNA and quantum computing to theoretical and applied machine learning, just to name a few. As a graduate student, you will: Access research-intensive lab spaces. Gain the opportunity to publish your work in top conferences and journals. Present at premier conferences in front of peers, industry leaders, researchers, and experts in your field. As a graduate student, you will have the independence to pursue your preferred area of research with a faculty If you want to continue pursuing research and expand your learning, you will work with a supervisor to develop a thesis. As a graduate student at the PhD level you will be expected to conduct meaningful research that expands the scope of your graduate work.<br><br>The SciCom group carries out research on methods and software for supporting applications in such areas as medical imaging, option pricing and hedging, portfolio optimization, biomedical modelling, computational neuroscience, and physically based animation. Group members develop and analyze algorithms for solution of large sparse matrices, large-scale optimization, least-squares problems, and numerical solution of partial differential equations. These algorithms are then tested in a variety of application domains. Each application brings specific computational difficulties and challenges. One of the challenges in scientific computation is to understand these computational difficulties and meet them with effective methods embedded in efficient software. Current collaborations with researchers and practitioners in finance, graphics, and medicine have helped the SciCom researchers to understand the computational requirements of these applications.
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