国际学生入学条件
A bachelor's degree or recognized equivalent from an accredited institution. If you are in your final year of studies and you expect to earn your degree by mid-August of the following year, you may apply. If you are admitted, you will be required to provide proof at that time that you have earned your bachelor's degree, usually in the form of a final official transcript. If you attended an American university or a university that uses a similar 4.0 scale, a satisfactory scholastic average with a minimum grade-point average (GPA) of 3.0 (B) is required. If you attended a university that does not use the 4.0 system, Three (3) Letters of Recommendation uploaded as PDFs through the link provided in the online application. Your letters could include details about your goals, research accomplishments, technical and leadership skills, academic work, etc. We suggest to give your recommenders at least a few weeks to write your letters. The General Test of the Graduate Record Examination (GRE). We do not have minimum or cutoff GRE test scores. Statement of Purpose, Personal History Statement, Unofficial Transcripts, Resume, All three sections of the GRE are required, The minimum TOEFL score required by UC Berkeley for graduate admission is 570 on the paper-based test (PBT), 230 on the computer based test (CBT), and 90 on the Internet Based Test (iBT). The minimum score for the IELTS is an overall band score of 7, there are no minimum scores for the individual bands. A grade point average of B or better (3.0).
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雅思考试总分
7.0
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- 雅思总分:7
- 托福网考总分:90
- 托福笔试总分:570
- 其他语言考试:NA
课程简介
Research covers theory, simulation, and implementation. We study the fundamental problems in information and coding theory, communication, data science, network science, optimization, statistics, machine learning, distributed systems, economics, statistical signal processing, and stochastic control. The motivations are guided by societally important applications such as data centers, distributed storage and content delivery, peer-to-peer computing, social networks, control over wireless networks, cognitive radio, spectrum sharing, scheduling, privacy and security, incentive and mechanism design with resource constraints, sensor networks, transportation systems, hybrid systems, systems biology, DNA and RNA sequencing and storage, and MRI. We develop and apply tools in probability theory, information and coding theory, functional analysis, convex geometry, queuing theory, stochastic processes, optimization theory, statistical physics, statistics, and game theory. We also research fundamental building blocks of large-scale communication and computing infrastructures.
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