国际学生入学条件
B.S. or B.A. degree in a quantitative field from an accredited institution
GRE and TOEFL scores for an applicant whose native language is not English
Official transcripts Test-takers should score at least 90 on the iBT (internet-based) TOEFL, at least 600 on the paper-based TOEFL or score 250 on the computer-based TOEFL. For students who choose to take the IELTS in lieu of TOEFL, the minimum score is 7. In general, applicants should have at least a 3.0 (B) grade point average, or the equivalent, in their undergraduate work.
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雅思考试总分
7.0
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雅思考试指南
- 雅思总分:7
- 托福网考总分:90
- 托福笔试总分:600
- 其他语言考试:Duolingo. A minimum score of 115 is required.
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
工业工程硕士(MIE)是一个专业的学位论文学位,要求31个学时的500级或更高级别的已批准课程,包括1个学时的最终项目。拥有工程学或相关研究领域的学士或学士学位的学生可以申请。完成MIE学位后,学生将能够:建立在现实世界中出现的复杂系统的物理和数学模型。通过物理或数学模型了解从制造到仓库再到客户的物料流。产生数据驱动的可实施解决方案,以提高实际系统的效率。将模型生成的解决方案和见解传达给非技术人员。工业工程提高了制造,服务,医疗,能源和物流中各种系统的效率和安全性。它使用数学和物理模型来做出每个主要经济部
The Master of Industrial Engineering (M.I.E.) is a professional nonthesis degree, requiring 31 credit hours of approved courses at the 500-level or above, including a final project of one credit hour. Students who have a B.A. or B.S. degree in any field of engineering or related study may apply. Upon completing the MIE degree, students will be able to: Build physical and mathematical models of complex systems that arise in real-world situations. Understand the flow of material from manufacturing to warehouses to customers through physical or mathematical models. Produce data-driven and implementable solutions that improve the efficiency of real-world systems. Communicate the solutions and insights generated by the models to a non-technical audience. Industrial engineering improves the efficiency and safety of various systems in manufacturing, services, health care, energy and logistics. It uses mathematical and physical models to make data-driven decisions needed in every major economic sector. The Professional Master's Program in Industrial Engineering at Rice is for students seeking a deeper understanding of how sophisticated decision models can optimize complex systems in any industry as well as the nonprofit sector.
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