计算机科学哲学博士
Doctor of Philosophy in Computer Science
  • 学历文凭

    Ph.D.

  • 专业院系

    计算机科学

  • 开学时间

    27 June 2024

  • 课程时长

    2 Semester(s)

  • 课程学费

    USD 58,974

    汇率提示

国际学生入学条件

Transcripts of prior higher education.
Applicants should have earned or expect to earn a master's degree in computer science. An applicant with a master's degree in electrical or computer engineering, mathematics or a related field will also be considered.
An outstanding student who has completed a bachelor's degree and has met all other entrance requirements may also be considered.
Results of the Graduate Record Examination (GRE) General Test.
Three letters of reference from persons able to assess the student's qualifications for doctoral-level study and likelihood of success. The department may also directly contact referees after the submission of the reference letters.
A resume that includes a description of academic background and professional experience.
An essay describing the applicant's academic and professional objectives.

IELTS - 6.5. TOEFL iBT - 80
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雅思考试总分

6.5

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  • 雅思总分:6.5
  • 托福网考总分:80
  • 托福笔试总分:160
  • 其他语言考试:Pearson Test of English, Academic Module (PTE) - 54 <br>Duolingo - 105
CRICOS代码:
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课程简介

该博士课程旨在培养具有计算机科学研究专业知识的计算机科学家。具体重点领域包括算法复杂性理论,人工智能,生物信息学,云计算,编译器优化,计算科学(生物学,化学,金融,数学/统计,医学,物理学),计算机体系结构,计算机图形学,计算机网络,计算机安全,数据分析,数据仓库和挖掘,分布式和移动数据库,嵌入式系统,正式规范和验证,人机交互和可视化,高性能计算,基于知识的系统,语言和自动机理论,数学和计算机建模,多媒体数据库和系统,神经网络,并行和分布式算法,模式识别和图像处理,科学计算和数值分析,模拟,软件工程和We
The doctoral program is designed to develop computer scientists with research expertise in computer science. Specific areas of emphasis include algorithmic complexity theory, artificial intelligence, bioinformatics, cloud computing, compiler optimization, computational science (biology, chemistry, finance, mathematics/statistics, medicine, physics), computer architecture, computer graphics, computer networking, computer security and privacy, cyber physical systems/internet of things, data analytics, data driven security analytics, data warehousing and mining, distributed and mobile data bases, embedded systems, human-computer interaction and visualization, high-performance computing, knowledge-based systems, language and automata theory, mathematical and computer modeling, multimedia databases and systems, neural networks, parallel and distributed algorithms, pattern recognition and image processing, pervasive systems, scientific computing and numerical analysis, simulation, smart connected communities, software engineering and web applications. The program also permits a student to acquire expertise in closely related fields such as computer engineering and mathematics.
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