Bachelor of Science in Computer Science and Molecular Biology

4 Years On Campus Bachelors Program

Massachusetts Institute of Technology

Program Overview

MIT’s Course 6-7 is a collaborative program between the Department of Electrical Engineering and Computer Science (EECS) and the Department of Biology. It integrates the analytical rigor of computer science with the empirical foundations of molecular biology, preparing students to tackle complex biological problems using computational tools.​

Core Modules

  • Mathematics & Programming

    • 6.100A: Introduction to Computer Science Programming in Python

    • 6.120A: Discrete Mathematics and Proof for Computer Science

    • 6.C06[J]: Linear Algebra and Optimization​

  • Chemistry

    • 5.12: Organic Chemistry I

    • 5.601: Thermodynamics

  • Introductory Laboratory

    • Options include:

      • 7.002 & 7.003[J]: Fundamentals and Applied Molecular Biology Laboratory (CI-M)

      • 20.109: Laboratory Fundamentals in Biological Engineering (CI-M)

  • Foundational Subjects

    • Computer Science:

      • 6.1010: Fundamentals of Programming

      • 6.1210: Introduction to Algorithms

      • 6.3900: Introduction to Machine Learning

    • Biological Sciences:

      • 7.03: Genetics

      • 7.05: General Biochemistry

      • 7.06: Cell Biology

  • Restricted Electives

    • Courses such as:

      • 6.8701: Computational Biology: Genomes, Networks, Evolution

      • 7.093 & 7.094: Communication in Experimental Biology (CI-M)

      • Electives from AI+D, Computational Biology, or Biology tracks

Experiential Learning (Research, Projects, Internships etc.)

MIT emphasizes hands-on learning, ensuring that students not only grasp theoretical concepts but also apply them in real-world contexts.​

  • Laboratory Courses

    • Courses like 7.003[J] and 20.109 provide practical experience in molecular biology techniques and experimental design.

  • Undergraduate Research Opportunities Program (UROP)

    • Students can engage in cutting-edge research projects across various labs, allowing them to contribute to ongoing scientific inquiries.​

  • Capstone Projects

    • Advanced undergraduate projects, such as 6.UAR (Seminar in Undergraduate Advanced Research), enable students to delve deep into specific topics, culminating in comprehensive reports and presentations.

  • 6A MEng Thesis Program

    • This program offers students the chance to work on industry-sponsored research projects, bridging academic learning with practical applications.​

Progression & Future Opportunities

Graduates of Course 6-7 are uniquely positioned at the intersection of biology and computer science, opening doors to diverse career paths:​

  • Computational Biology & Bioinformatics

    • Roles in analyzing genomic data, developing algorithms for biological data interpretation, and modeling biological systems.​

  • Pharmaceutical & Biotechnology Industries

    • Positions in drug discovery, personalized medicine, and the development of diagnostic tools.​

  • Software Engineering & Data Science

    • Opportunities in tech companies focusing on healthcare solutions, bioinformatics platforms, and data analysis tools.​

  • Academic & Clinical Research

    • Pursuing graduate studies or research positions in areas like systems biology, molecular genetics, or computational neuroscience.​

  • Healthcare & Medicine

    • With the foundational knowledge in biology and computational tools, graduates can transition into medical fields, especially those emphasizing precision medicine.​

Program Key Stats

$61,990
$ 75
Aug Intake : RD 6th Jan EA/ED 1st Nov


8 %
No
Yes

Eligibility Criteria

AAA - A*A*A*
3.5 - 4.0
38 - 42
90 - 95

1510 - 1580
34 - 36
7.0
90

Additional Information & Requirements

Career Options

  • Career Pathway: Computer Science & Molecular Biology (Course 6-7)   Computational Biology & Bioinformatics Bioinformatics Analyst Computational Biologist Genomics Data Scientist Systems Biologist   Software & Health-Tech Engineering Software Developer (Biomedical Tools) Full-Stack Engineer (Biotech Startups) Cloud-Based Health App Developer Algorithm Engineer (Genetic Platforms)   AI
  • Data Science & Machine Learning in Biomedicine Machine Learning Engineer (Biotech Focus) Biomedical Data Scientist AI Researcher (Drug Discovery / Diagnostics) Deep Learning Engineer (Precision Medicine)   Biotech & Pharmaceutical Industry R&D Scientist (Biotech Firms) Pharmacogenomics Analyst Clinical Informatics Specialist Molecular Modeler   Academic & Scientific Research Research Assistant / Scientist PhD in Computational Biology / Bioengineering Academic Technologist Research Software Developer   Healthcare & Clinical Genomics Clinical Genomics Specialist Medical Informatics Consultant Digital Pathology Analyst Medical Data Engineer   Entrepreneurship & Innovation Bio-entrepreneur Founder
  • Biotech or Health-Tech Startup Scientific Product Designer Venture Analyst (Biotech-focused VC firms)   Further Studies MS or PhD in: Computational Biology Molecular Genetics AI in Healthcare MD-PhD (for Clinical Research careers) MBA (for Tech/Bio Startups or Biotech Management)   Long-Term Growth Computational Biology: Analyst → Lead Scientist → Director of Bioinformatics AI in Biomedicine: ML Engineer → AI Team Lead → Chief AI Officer Tech + Bio: Software Dev → Bioinformatics PM → CTO (Bio-Tech) Startup Path: Founder → Seed Stage → Series B → CEO

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