Become an MSSE Partner
Collaborate with students to develop scalable computational software and solve problems in the molecular sciences.
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.
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 sbutcher@berkeley.edu.
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:
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.
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.
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
Students Assigned to Capstone Projects
Capstone Begins
Capstone Ends
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
FAQ
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: https://kraken.molssi.org/home
Learn More
To learn more or propose a project, get in touch with our Executive Director, Sean Butcher at sbutcher@berkeley.edu.