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工程与应用科学

生物技术创新与计算

 学校:  

卡内基梅隆大学

   硕士生项目

Master of Science in Biotechnology Innovation and Computation program

标准考试成绩要求

TOFEL:100

IELTS:7.5

学年学制

84 units

学年学费

暂无

奖学政策

暂无

所在校区

暂无

专业排名

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招生人数

暂无

录取要求

To apply to the MSBIC, you must have:
Applications will be accepted starting in September for the next Fall  class.
A cumulative grade point average higher than 3.4
Scores from Graduate Record Examination (GRE).
Scores from the Test of English as a Foreign Language (TOEFL). (For Non-Native English speaking students)
If you have previously taken the GRE, your scores will be accepted if they are less than five years old.
If you have previously taken the TOEFL, your scores will be accepted if they are less than two years old.
Your English language test score should indicate proficiency (TOEFL > 100). We have found that English language proficiency has a very large impact on a student’s success with the program.
Submit your current Resume. Outline your education, work experience, publications (if any), scholarships awarded, prizes and honors received, society memberships, and any other extracurricular activities.
Prepare a Statement of Purpose. Type or print neatly a concise one- or two-page statement in this format:
Part I: Briefly state your objective in pursuing a professional graduate degree in MSBIC. Tell us if you have a particular reason for applying to this degree.
Part II: Describe your background in fields particularly relevant to your objective. List here any relevant academic, industrial or commercial experience.
Part III: Include any additional information you wish to supply to the Admissions Committee.
Submit unofficial transcripts from all undergraduate and graduate institutions attended.
Upload three letters of recommendation. The admissions committee prefers, but does not require, letters from both academia and industry. People who recommend you should know you relatively well and should be able to discuss the quality of your work.
To submit the application click here.
Send any off-line material to:
 

Charles Burger
School of Computer Science
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213-3891 USA

申请材料清单

What are the admission criteria for this program?

Like many master degree programs at CMU, the MSBIC program is very selective. Our focus is on the quality of our students and the quality of the educational experience. Most of our admitted students have degree in Computer Science, Software Engineering.
English language competency is strongly correlated to academic and professional success. Thus the degree program has a minimum English competency score requirement. A successful applicant will normally have a minimum TOEFL score of 100 or an IELTS score of at least 7.5.
The program has a minimum GRE requirement (Verbal . 160, Quant – 165). However, academic performance is the strongest predictor of success in the degree program. We prefer applicants to have minimum GPA of 3.5 or higher.

The application requires a personal essay for the application. What makes a good essay?

We are looking for strong evidence that you can do well in our degree program. For example, a description of your academic experience, your achievement in these courses project, is good evidence. A description of a software project, your involvement in the project, and the impact of the project is good evidence. Please write the essay yourself. Get help of course, but it should be substantially your own words.

The application requires letters of recommendation. What makes a good letter?

The strongest letters come from respected advisors, managers and professors who know your work and who write favorably about your work. Although no work experience is required for admission. However, we value some types of work experience, particularly if the experience is close to the type of work our graduates perform.

What about internships?

Internships provide an opportunity for an industrial development or industrial experience before graduation. This experience improves the student’s access to the company providing the internship and generally improves the student’s employment prospects. We encourage students to do an internship.

截止申请时间:

rolling

专业介绍

Carnegie Mellon’s Master of Science in Biotechnology Innovation and Computation program follows a unique educational paradigm that combines a rigorous computer science education with real-world experience in initiating and operating an entrepreneurial project with external stakeholders. BIC students often become successful entrepreneurs armed with a wealth of practical skills, experience, and concrete value-creation capabilities. Those who choose to take a position with an established company enter the market as professionals trained in the latest generation of computational and data engineering technology and best practices. BIC graduates are perfectly poised to create immediate value in any startup or established organization.

Our students apply techniques from machine learning, big data analytics, data mining and information retrieval to solve important problems in a wide range of domains. They learn to solve these problems by correctly capturing the information need, identifying resources, designing analytic pipelines, coding required modules and integrating emerging technologies into an effective solution. Once they hit the workforce, our graduates can quickly assemble teams, identify challenges and create innovative solutions to problems. BIC students have founded several successful startups from the projects they worked on within the program. For those who did not choose the entrepreneurial path, our graduates boast the highest average starting salaries of any professional master’s program at Carnegie Mellon in 2013, 2014 and 2015, and we currently have a 100 percent placement rate. Our alumni are data scientists, software engineers, and technical executives in the software, manufacturing and bio-science industries.

课程设置

  • 1) The Core Courses (72 units – must be taken in sequence):
  • 02-651 – New Technologies and Future Market (12 units)
  • 11-695 – Competitive Engineering (12 units)
  • 02-654 – Biotechnology Enterprise Development (12 units)
  • 11-691 – Capstone Project (36 units)
  • 2) The Knowledge Area Courses (84 units):
  • 10-600 – Math for Machine Learning (12 units)
  • 11-601 –   Coding Boot Camp (12 units)
  • 10-601 –  Machine Learning (12 units)
  • 11-675  –  Big Data Systems in Practice (12 units)
  • 02-750 –  Automation of Research/Machine Learning Robotics  (12 units)
  • 02-604 – Fundamentals of Bioinformatics (12 units)
  • Students can select one out of the following three courses:
  • 02-613 – Advanced Algorithm & Data Structure (12 units)
  • 15-513  – Introduction to Computer Systems (12 units) Or
  • 11-611   – Natural Language Processing (12 units)
  • 3) Electives (36 units):
  • A minimum of 36 units of LTI, CBD or SCS courses must be taken.
  • Examples include but are not limited to:
  • 02-710 – Computational Genomics (12 units)
  • 02-712 – Computational Methods for Biological Modeling (12 units)
  • 02-730 – Cell and Systems Modeling (12 units)
  • 11-411 – Natural Language Processing (12 units)
  • 11-676 – Big Data Analytics (12 units)
  • 11-642 – Search Engines (12 units)
  • 15-619 – Cloud Computing (12 units)
  • 17-637 – Web Application Development (12 units)
  • 15-615 – Database Applications (12 units)
  • 15-640 – Distributed Systems (12 units)
  • 15-645 – Database Systems
  • 11-741 – Information Retrieval (12 units)
  • 15-826 – Multi-Media Web Mining (12 units)
  • 11-661 – Languages and Statistics (12 units)
  • 11-683 – Mathematical Foundations for Data Science (12 units)
  • 10-605 – Machine Learning With Large Data Sets (12 units)
  • 11-755 – Machine Learning Using Signal Processing (12 units)
  • 11-643 – Machine Learning in Text Mining (12 units)
卡内基梅隆大学攻略

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