Doctor of Philosophy in Computer Science and Engineering - Data and Software Systems-内华达大学雷诺分校申请条件

Doctor of Philosophy in Computer Science and Engineering - Data and Software Systems

内华达大学雷诺分校

University of Nevada Reno

美国

学历文凭
Ph.D.
专业院系
Department of Computer Science and Engineering
开学时间
课程时长
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国际学生入学条件

Applicants to the doctoral degree program should have a bachelor’s degree in engineering, mathematics, or science and have minimum experience that includes the equivalent of a Computer Science and Engineering minor. Applicants should further meet the following minimum criteria and the materials for admission: A minimum undergraduate GPA of 3.25 if the applicant does not have an M.S. degree or a minimum undergraduate GPA of 3.0 if the applicant has an M.S. degree. A minimum TOEFL score of 79 PBT- 550, Duolingo score of 105, or IELTS score of 6.5 for international applicants. A one-page personal statement describing research interests and career goals. Candidates are expected to clearly indicate their research interests as well as the faculty members they are interested in working with. Three letters of recommendation.

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IDP—雅思考试联合主办方
雅思考试总分
6.5

雅思总分：6.5
托福网考总分：79
托福笔试总分：550
其他语言考试：Pearson (PTE): 59, Cambridge: 176, Duolingo: 105

CRICOS代码：
申请截止日期：请与IDP联系以获取详细信息。

课程简介

Researchers in data and software systems are developing computational and software solutions to advance the collection and use of big data for scientific research. Research in this area also focuses on enhancing human-computer interaction and facilitating data and software-intensive interdisciplinary projects.<br><br>Faculty specializing in software systems are leveraging the power of modern computing and technology to develop new techniques and tools that increase productivity in research projects and industrial applications. Research in human-computer interaction focuses on developing new locomotion techniques for navigation in virtual reality and new ways of interacting, such as brain-computer interfaces.<br><br>In big data, we aim to advance fundamental data-centric research and data-driven domain discoveries, build data infrastructure for scientific research, and develop a 21st-century data-skilled workforce, which is in very high demand.

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