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Master of Science Engineering in Electrical Engineering (MSE)

德克萨斯大学里奥格兰德河谷分校

University of Texas Rio Grande Valley

US美国

  • 学历文凭

    学历文凭

    Masters Degree

  • 专业院系

    专业院系

    Department of Electrical Engineering

  • 开学时间

    开学时间

  • 课程时长

    课程时长

  • 课程学费

    课程学费

    汇率提示

国际学生入学条件

To be admitted to the graduate program in electrical engineering with clear admission status, prospective candidates must first meet all requirements for graduate admission to UT Rio Grande Valley, as well as the other requirements listed below:
GRE General Test. GRE test scores are valid for 5 years. A waiver of the GRE requirement will be granted to applicants who show proof of completing a graduate degree (master's or doctoral).
Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, Mathematics, or similarly named program with content equivalent to an Accreditation Board for Engineering and Technology (ABET)-accredited BS in Electrical Engineering.
Admitted applicants that do not have an undergraduate degree in Electrical or Computer Engineering, or in a similar field are usually required to take undergraduate leveling courses as pre-requisites of our graduate courses.
Undergraduate GPA of at least 3.0 in the last 60 semester credit hours.
Letter of Intent detailing professional goals and reasons for pursuing the graduate degree.
Resume.

IELTS 6.5
TOFEL ibt 79
TOFEL pbt 550
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  • 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:Duolingo English Test - 105

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课程简介

The Master of Science in Engineering degree has a thesis option and a non-thesis option. Coursework is offered in areas including computer engineering, power and energy, systems and controls, communications, digital systems, electronics, nanotechnology, and electromagnetics. Research opportunities are offered in power systems, renewable energy, smart grids, computer architecture and high performance computing systems, computer networks and cybersecurity, multimedia processors, VLSI/IC design and implementation, wireless communications, microwave and antenna engineering, radar imaging, electromagnetic applications, metamaterials, control systems and robotics, signal and image processing, advanced digital system design and testing, biomedical engineering and devices, sensors/electronics and detection, photonics and optics, nanotechnology and MEMS, big data, IoT, and machine learning.
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