Master of Molecular Science and Software Engineering
Online professional master’s program focused on teaching scientists to use computation and machine learning to solve real-world problems in the molecular sciences and beyond.
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Transform your science degree into a rewarding career
The Master of Molecular Science and Software Engineering (MSSE) is designed to train scientists and engineers in Software Engineering and Machine Learning.
The degree focuses on the molecular sciences and is suitable for students pursuing software engineering or data science roles in other areas requiring advanced machine learning, software engineering, complex mathematical modeling and simulations, or high-performance computing.
Skills You Will Learn
The skills that the MSSE teaches are directly transferable to other science and non-science based industries that require advanced machine learning, complex mathematical modeling and simulations, software engineering, or high-performance computing. MSSE is also an excellent preparation for students planning to pursue PhDs in the computational sciences.
MSSE Courses Combine
Computing
Science
Machine Learning
Explore Careers with MSSE
With its focus on Computational Molecular Science, MSSE prepares you for Software Engineering, Data Science, Machine Learning, and Research Scientist roles in high-demand fields such as Computational Chemistry, Cheminformatics, Computational Biology and Biochemistry, Bioinformatics, Computational Physics, Computational Material Science, Quantum Computational Chemistry, Nanotechnology, and other Computational Science fields.
Computational Scientists
Average Starting Salary $119,850
Machine Learning Engineers
Average Starting Salary $124,742
Simulation and Modeling Engineer
Average Starting Salary $111,900
Software Engineer
Average Starting Salary $118,997
Computational Chemist
Average Starting Salary $110,035
AI Engineer
Average Starting Salary $127,374
Online Learning
MSSE courses are taught online, except for two on-campus bootcamps*. Online Learning at Berkeley means you can receive a Berkeley-quality education from anywhere in the world—no visa application required. The MSSE features small classes taught by world-renowned faculty.
*Fully online options are available.
Finish The Program
Full-Time
Finish the MSSE degree fast in 9-months
or two semesters.
OR
Part-Time
Earn your master’s in two years or
on your own schedule.
Applications are open for a Fall 2024 program start! Apply by February 1st, 2024.
Transform Science-Based Industries
The MSSE’s curriculum teaches computational molecular science with a focus on advanced machine learning, complex mathematical modeling and simulations, software engineering, and high-performance computing. These skills are increasingly used across a wide range of science-based industries including:
Biotech & Pharmaceutical
$3.8 Trillion
- Drug discovery and new therapeutics
- Vaccine development
- Individualized medicines
- Improved testing and screening
Materials
$1.9 Trillion
- Renewable bioplastics
- Reliable, durable materials for renewables
- Biocompatible materials
Energy
$3.5 Trillion
- Renewable energy & biofuels
- Eco-friendly materials & chemical processes
- Improved solar cells
- New battery technologies
Food & Agriculture
$1 Trillion
- Food and water security
- Decarbonizing the synthesis of chemical feedstocks
- New water treatment technologies
Semiconductors
$1.9 Trillion
- Developing advanced semi-conductor materials
- Thermal condoctivity improvements
- Improving yield and cost
Aerospace
$.7 Trillion
- Lighter, stronger, more durable materials
- Superalloys and exotic materials
- Shape memory and superelastic alloys
Solving Global Challenges
Some of the world’s largest challenges can be addressed at the molecular level and computational molecular science will be a key component in this endeavor.
Climate Change
- Eco-friendly materials and chemical processes
- Low-carbon generation of hydrogen and other related energy carriers
- Renewable bioplastics
- Carbon Capture technologies
- Decarbonising the synthesis of chemical feedstocks
- Exascale computing to better model the world climate system
Food and Water Security
- Increased crops yields
- Reduced pest associated losses
- Increased nutritional values of foods
- New water treatment technologies to meet the growing demand for dwindling supplies
Health & Aging
- Drug discovery
- New therapeutics
- Vaccines
- Individualized medicine
- Biocompatible materials
- Improved testing & screening
- Better understanding of biological processes
Renewable Energy
- Improved solar cells
- New battery technologies
- Biofuels
Key Concepts
Computational molecular science is becoming widely used in the chemical, biochemical, and material sciences. Traditional material-development processes can take 10 to 20 years to bring a new material to market. Computational science has the potential to dramatically cut the time it takes to move a molecule or material from the lab to a product.
Computational Science
Harnesses computers and mathematical modeling to understand and solve complex problems in science and engineering. Its applications can range in size from the interaction of individual atoms to the behavior of weather systems and galaxies.
Molecular Science
Molecular science seeks to explore the properties and interactions of molecules at atomic, molecular, supramolecular, and system levels to develop new materials and useful interactions that solve real-world issues such as disease, world hunger, renewable energy, and environmental problems. Molecular science unifies the fields of chemistry, physics, biology, and the material sciences.
Computational Molecular Science
Combines software engineering and theoretical molecular science to model, analyze, and simulate molecular structures, properties, and interactions. The field uses specialized hardware and software, algorithm design, and large-scale data management to perform algorithmically complex, data-intensive modeling and analysis tasks.
As computational power continues to grow rapidly and as more advanced software tools and techniques become available the importance of computational molecular science to industrial and academic research will continue to grow.
High Performance Computing (HPC)
HPC enables the processing of complex calculations that use large amounts of data at high speeds. HPC typically involves using hundreds or sometimes thousands of computers or processors in parallel. This allows users to run large analytical computations, with millions of scenarios, that can use terabytes of data. HPC is used extensively in the computational molecular sciences.