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About MSSE

UC Berkeley’s Master of Molecular Science and Software Engineering (MSSE) prepares students with a background in chemistry, physics, biology, engineering, and computer science for careers in computational science, data science, machine learning, and software engineering. To learn more: view our curriculum.

The Capstone Project

At the end of the program, students partner with companies and labs to address complex and challenging machine learning and software engineering problems. Projects may be self-contained or part of a larger business initiative. Supervised by a faculty member, students will spend 10 hours a week working on their capstone for 16 weeks during their last spring semester.

Learn More

To learn more or propose a project, get in touch with our Executive Director, Sean Butcher at

Project Tracks

Projects may consist of software development, machine learning, mathematical modeling and simulations, and high-performance computing. Given the wide variety of student backgrounds, professional interests, and computational science topics covered in the MSSE program, the capstone projects will be classified into one of the following three professional interdisciplinary tracks:

1. Scientific Problem.

A project on this track focuses on the research and development of a computational science application. Students understand the scientific problem at hand and the impact that their project will have in a particular field of science.

2. Large Scale Computing.

A project on this track focuses on the development of large-scale software libraries, tools, or computational applications relevant to molecular science. Students understand the need for scaling a given computational application, the computational complexity of applications and key kernels, and the impact that the project deliverables will have in a particular field of science.

3.Software Engineering and Algorithms.

A project on this track focuses on the development of a library or software package for computational sciences applying the best practices of software engineering and covering all elements of the software engineering cycle. Students understand the need for such a library or service to the computational science community.

Capstone Partnership Timeline


Project Proposal Period Begins


Project Proposal Period Closes


Projects Recommended to Students

Faculty committee recommends students to partner organizations.


Students Assigned to Capstone Projects

Companies can interview the candidates and decide whether to move forward with them. NDAs and IP agreements established if necessary.


Capstone Begins

MSSE faculty mentors supervise each capstone's developmental milestones.


Capstone Ends

Student team prepares and presents final report to stakeholders.

Curriculum Highlights

  • Software Engineering
  • C++, Python
  • Computational Science
  • Machine Learning
  • Data Science
  • Deep Learning
  • Mathematical Modeling & Simulations
  • Molecular Science
  • Data Visualization
  • High Performance Computing
  • Computational Quantum Chemistry


Submit a job posting by emailing us at Many students take the program part-time while working full or part time, and may be job searching at any time of year.

Typically 2-5 students will work on each capstone project. The number will depend on the scope of the project along with student interest.

The University will sign a non-disclosure agreement with the partner organization on behalf of its faculty and staff. In addition, the partner organization can require the students to sign NDA’s as a condition of working on the capstone project. Any IP generated by the capstone team for the project is retained by the partner organization.

An Open-Source Web-Application for Molecular Science Software Libraries and Databases.
by Usman Jamshed, Supervisor Dr. Jesica Nash, Molecular Software Science Institute.

Artificial intelligence and machine learning have greatly accelerated the rate of molecular discovery. However, the distribution and availability of data for these molecules still need to be improved. We have developed an open-source web application for molecular libraries and databases to address this challenge. The application uses containerization (Docker) and open-source libraries to create a modular and extensible platform for accessing molecular descriptors. This effort will streamline the accessibility to descriptor data necessary for computational advancements. The new web application is easy to use, visually appealing, and packed with features that will make it a valuable resource for academic and industry researchers.

Project's site:

Faculty mentors will solicit feedback from project partners during the course of the capstone and will assist in the development and check-in of milestones. MSSE students will receive a grade for their capstone and feedback from the partner organization will be weighted in their final grades.

No. Students receive course credit for their capstone and are not paid.

Learn More

To learn more or propose a project, get in touch with our Executive Director, Sean Butcher at