1

Computational Science Jobs in Berkeley, CA (NOW HIRING)

Computational Biologist

San Francisco, CA · On-site

$125K - $185K/yr

Computational biologist role We're hiring a computational biologist to analyze our patients' omics ... This role sits at the intersection of cutting-edge science and real-world clinical impact: you'll ...

Computational biologist role We\'re hiring a computational biologist to analyze our patients' omics ... This role sits at the intersection of cutting-edge science and real-world clinical impact: you\'ll ...

Showing results 21-40

Computational Science information

See Berkeley, CA salary details

$68.9K

$101.3K

$119.5K

How much do computational science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for computational science in Berkeley, CA is $101,318.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $114,000.00 per year, depending on experience, location, and employer.

What is computational science?

Computational science is an interdisciplinary field that uses advanced computing capabilities to understand and solve complex problems. It combines elements of mathematics, computer science, and domain-specific knowledge to create simulations, analyze data, and model physical, biological, or social systems. Computational scientists develop algorithms and use high-performance computing to tackle problems that are difficult or impossible to solve analytically. This field is essential in areas such as climate modeling, drug discovery, engineering, and physics.

What are the key skills and qualifications needed to thrive as a computational scientist, and why are they important?

To thrive as a Computational Scientist, you need a strong background in mathematics, programming (such as Python, C++, or MATLAB), and domain-specific scientific knowledge, often supported by an advanced degree in a relevant field. Familiarity with high-performance computing (HPC) systems, parallel processing frameworks, and scientific data analysis tools is typically required. Excellent problem-solving skills, collaboration, and effective communication set top candidates apart in interdisciplinary research environments. These skills and qualities are crucial for driving innovative scientific discovery and translating complex data into actionable insights.

What are some common challenges faced by computational scientists when working on interdisciplinary projects?

Computational scientists often collaborate with experts from fields like biology, physics, or engineering, which can present challenges in bridging gaps in domain-specific knowledge and communication styles. Adapting computational models to fit the unique requirements of different disciplines, while ensuring accuracy and efficiency, is a frequent hurdle. Additionally, managing large datasets and integrating diverse computational tools requires strong technical and organizational skills. Open communication and a willingness to learn from colleagues are key to overcoming these challenges and achieving successful project outcomes.

What is the difference between Computational Science vs Data Scientist?

AspectComputational ScienceData Scientist
Required CredentialsDegree in science, engineering, or computational fields; often requires advanced degreesDegree in statistics, computer science, or related fields; often requires knowledge of programming and analytics
Work EnvironmentResearch labs, universities, industry R&D departmentsTech companies, finance, healthcare, consulting firms
Industry UsageScientific research, simulation, modelingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

Computational Science focuses on developing models and simulations to solve scientific and engineering problems, often requiring advanced degrees and research environments. Data Scientists analyze large datasets to extract insights and support decision-making, typically working in business or tech sectors. While both roles involve programming and data handling, their primary goals and work settings differ significantly.

Is computational science a good career?

Computational science is a viable career that involves using computer models, simulations, and data analysis to solve complex scientific problems. It typically requires strong skills in programming, mathematics, and domain knowledge, and offers opportunities in research, industry, and academia with competitive salaries and growth potential.

What can you do with a computational science degree?

A computational science degree prepares individuals for roles such as computational scientist, data analyst, simulation engineer, or research scientist. Graduates often work in industries like technology, healthcare, finance, or government, utilizing skills in programming, modeling, and data analysis to solve complex problems. Knowledge of tools like Python, MATLAB, or high-performance computing environments is also valuable.

What are popular job titles related to Computational Science jobs in Berkeley, CA?

For Computational Science jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Computational Science jobs in Berkeley, CA look for?

The top searched job categories for Computational Science jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Computational Science jobs?

Cities near Berkeley, CA with the most Computational Science job openings:

Infographic showing various Computational Science job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 77% Physical, 4% Hybrid, and 19% Remote job distribution, with an average salary of $101,318 per year, or $48.7 per hour.

Computational Neuroscientist, Modeling / Theory

Astera Institute

Alameda, CA • On-site

$150K - $300K/yr

Full-time

Posted 16 days ago


Job description

Company Overview

Astera Neuro seeks to understand and engineer consciousness. We believe consciousness is the process by which the brain builds a coherent internal model of the world and the self. We aim to understand this model and to develop the technologies to write experience directly into the brain. By combining large-scale neural recording, causal perturbation, and brain-based AI, we seek to move neuroscience from observing correlates of experience to engineering it. The same tools carry direct therapeutic promise for neurological and psychiatric diseases that alter perception, thought, and sense of self. Because the science and tools required do not yet exist, we are assembling a founding team of neuroscientists, theorists, and engineers to create them. We do high-risk, high-reward science in a well-resourced, collaborative environment with competitive pay, and share everything openly under Astera's Open Science Policy.

Position Summary

Computational Neuroscientists at Astera Neuro develop and lead research programs aimed at understanding the representations and dynamics underlying conscious access, and at converting that understanding into the ability to steer the system. The work sits at the intersection of cognitive theory, large-scale neural data, and machine learning, and draws on recordings from our primate, rodent, and human programs. The opportunity here is to create an entirely new theoretical framework for how the brain builds an internal model of the world, on data of a scale, breadth, and quality that has not previously existed.

Computation sits at the vital core of Astera Neuro. The role is built around tight coupling with experiment; models are expected to make testable predictions, and to propose the next experiment rather than wait for it. Title and scope are calibrated to track record.

Successful applicants will focus on one or more of Astera Neuro’s primary research tracks, with background and interest helping determine the best fit. Some positions suit scientists with a bent for modeling large-scale neural data, extracting structure from recordings that span many areas, sessions, animals, and species. Others suit scientists with a more theoretical bent, concerned with abstracting the key computational principles out of the data and into new NeuroAI architectures. We welcome computational scientists trained outside neuroscience; backgrounds in control theory, robotics, theoretical physics, statistics, and machine learning are all highly valued here.

What You’ll Do

  • Build models of compositional neural representation, grounded in cognitive theory and fit to recordings: how the brain binds content to variables, composes structured thought, and updates it.

  • Build coupled dynamical-systems models of the interactions between multiple brain areas, and test them against simultaneous multi-area recordings.

  • Analyze the fixed-point structure of these systems and characterize the landscape of stable states underlying percepts, thoughts, and internal states.

  • Derive how to sculpt inputs, using our optogenetic and electrical stimulation technology, to drive the system to chosen stable points, and validate those derivations in closed-loop write-in experiments.

  • Stitch data together across subjects and species into foundation models of neural activity, registered onto a common whole-brain functional and anatomical atlas.

  • Propose and help design new experiments: identify the measurement or perturbation that would most sharply separate competing models, and work with the experimental teams to run it.

  • Abstract key computational principles from the data into new NeuroAI architectures, in some cases in direct collaboration with Astera AI.

  • Mentor research engineers and, at the senior or principal level, more junior scientists; contribute to hiring, onboarding, and lab culture.

  • Contribute to publications, talks, open data and tooling releases, and engagement with the broader scientific community.

Who You Are

Required:

  • PhD with 3-12+ years of experience in computational neuroscience, neuroscience, physics, statistics, applied mathematics, electrical engineering, computer science, control theory, robotics, or a related field, or equivalent research experience. Graduate work or research experience in neuroscience is a plus but not required.

  • Demonstrated ability to lead a computational or theoretical research project end to end, from question and formulation through implementation, analysis, and publication.

  • Depth in dynamical systems, including fixed-point and attractor analysis, stability and bifurcation structure, and the fitting of dynamical models to noisy, partially observed data.

  • Strong computational skills, with fluency in Python and modern machine learning frameworks such as PyTorch or JAX, and comfort with large-scale data pipelines.

  • Hands-on experience analyzing large-scale neural datasets from electrophysiology, two-photon imaging, or comparable methods, including high-density recordings such as Neuropixels and modern spike-sorting and quality-control pipelines such as Kilosort.

  • Ability to work at close quarters with experimental neuroscientists, software engineers, and hardware engineers in a fast-moving, multi-team environment.

Preferred/Nice to Have:

  • Experience with latent-variable and state-space models of neural population activity, such as GPFA, LFADS, switching state-space models, or recurrent network models fit to data.

  • Background in control theory, optimal control, or robotics, particularly as applied to steering high-dimensional systems toward target states.

  • Background in statistics or theoretical physics, with a serious interest in applying it to neural systems.

  • Experience designing or implementing real-time or closed-loop decoders and model-guided stimulation.

  • Experience with foundation-model and self-supervised approaches applied to neural or behavioral data, and interest in the correspondence between artificial and biological representations.

  • Contributions to open-source neuroscience or scientific computing projects.

What We Value

  • Conviction that the brain’s internal model can be understood in full, and recognition that getting there requires a kind of science no single academic lab can do.

  • Appetite for building theory rather than applying it: the framework that explains how a physical system converges on a stable internal model of the world doesn’t yet exist, and we’re looking for people who want to build it.

  • Willingness to be held to an engineering standard: our decisive tests are write-in experiments, not merely decoding. What we cannot build, we do not understand.

  • Comfort building on shared infrastructure rather than private projects.

  • Commitment to open science.

Additionally Expected at Senior / Principal Level

  • Track record of owning a modeling or theory agenda end to end, including framing the question, collaborating with experimentalists, and delivering results.

  • Experience making and defending modeling tradeoffs across interpretability, predictive accuracy, and experimental utility.

  • Comfort working across the stack, from data infrastructure and analysis pipelines through to theory and machine learning.

  • History of mentoring scientists or leading technical initiatives (Principal level).

Why Join Us

Computational Neuroscientist at Astera Neuro, focused on answering the hardest and least understood questions in neuroscience: how the brain generates thoughts, intelligence, and consciousness. We seek to understand the compositional structure of neural representations and the dynamics that give rise to conscious access, and to build the theory that explains how a physical system converges on a stable internal model of the world.

Astera Neuro provides a comprehensive benefits package and total compensation that is competitive and commensurate with the level of experience and qualifications.

We are an equal opportunity employer and value diversity and inclusion!

Compensation Range: $150K - $300K