Explore MSSE

Transform your Science Degree

UC Berkeley’s MSSE prepares you for careers in computational science, data science, machine learning, and software engineering. The program is designed to train students with backgrounds in chemistry, physics, biology, engineering, computer science, or from other physical science disciplines.

Develop In-Demand Skills

Software Engineering
Computational Science
Machine Learning
Deep Learning
Data Visualization
Computational Quantum Chemistry
High Performance Computing
Leadership, Management, & Entrepreneurship

Invest in Your Career

Computational Scientists

Average Starting Salary $119,850

Machine Learning Engineers

Average Starting Salary $124,742

Computational Chemist

Average Starting Salary $110,035

           

Bioinformatics Engineer

Average Starting Salary $117,928

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:

$3.8

Trillion

Biotech & Pharmaceutical

$1.9

Trillion

Materials

$3.5

Trillion

Energy

$1

Trillion

Food and Agriculture

$1.9

Trillion

Semiconductors

$.7

Trillion

Aerospace

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

Renewable Energy

  • Improved solar cells
  • New battery technologies
  • Biofuels

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

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.

Go Beyond the Sciences

While the MSSE degree focuses on the molecular sciences, the skills it teaches are in high demand by other science and non-science based industries. Jobs in Data Science are predicted to grow by 31% over the next 10 years*. New jobs for Individuals with skills in artificial intelligence, advanced machine learning, and high performance computing are expected to be in even greater demand with 12 million new jobs being created across 26 countries by 2025.**

Non-science based industries where individuals with skills in advanced machine learning, complex mathematical modeling and simulations, software engineering, or high-performance computing are in high demand include:

$1.6

Trillion

Auto Manufacturing

$3.2

Trillion

Retail

$9

Trillion

Finance

$12.7

Trillion

Technology

$4.7

Trillion

Industrials

$7.4

Trillion

Healthcare

$6.4

Trillion

Communication Services

*US Bureau of Labor 2021
** World Economic Forum, Future of Jobs Report 2020
Figures based on 2022 US Stock Exchange Industry Sector Market Capitalization

Applications for Fall 2023 are open & due January 27th, 2023.

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