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Computational Cognitive Science Jobs in California

Voltai, Inc

Computational Scientist

Palo Alto, CA · On-site

... human cognitive limits. About the Team Backed by Silicon Valley's top investors, Stanford ... Solid understanding of AI for Science methodology: how to design datasets from simulations, handle ...

Voltai

Computational Scientist

Palo Alto, CA · On-site

... human cognitive limits. About the Team Backed by Silicon Valley's top investors, Stanford ... Solid understanding of AI for Science methodology: how to design datasets from simulations, handle ...

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Computational Cognitive Science information

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$36K

$64.6K

$119.9K

How much do computational cognitive science jobs pay per year?

As of Aug 23, 2026, the average yearly pay for computational cognitive science in California is $64,613.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,800.00 and $68,600.00 per year, depending on experience, location, and employer.

What is a computational cognitive science?

A Computational Cognitive Science job involves using computational models, artificial intelligence, and data analysis to study human cognition, including learning, reasoning, perception, and decision-making. Professionals in this field work at the intersection of cognitive psychology, neuroscience, and computer science to develop simulations and algorithms that mimic human thought processes. They may apply their expertise in academia, tech companies, healthcare, or AI research, contributing to advancements in human-computer interaction, machine learning, and cognitive system design.

What are the key skills and qualifications needed to thrive in computational cognitive science?

To thrive in Computational Cognitive Science, a strong background in cognitive psychology, computer science, and mathematics—often supported by a relevant advanced degree—is essential. Experience with data analysis software (such as Python, R, or MATLAB), machine learning libraries, and experimental design tools is typically expected. Critical thinking, interdisciplinary collaboration, and effective communication are crucial soft skills for success in this field. These abilities enable professionals to design robust experiments, analyze complex data, and translate insights into impactful research or product developments.

What are the most common challenges faced by professionals in computational cognitive science?

One of the main challenges in Computational Cognitive Science is integrating knowledge from multiple disciplines such as psychology, neuroscience, and computer science to build and validate complex models of human cognition. Professionals often have to balance rigorous experimental design with advanced computational techniques, all while staying current with rapidly evolving technologies and research findings. Collaboration with diverse teams—including software engineers, data scientists, and behavioral researchers—is common and may require adjusting communication styles to bridge knowledge gaps. Successfully navigating these challenges can make a significant impact in both academic and industry settings, leading to advancements in artificial intelligence, user experience design, and human-computer interaction.

Is computational cognitive science a good career?

Computational cognitive science is a multidisciplinary field combining psychology, computer science, and neuroscience, with careers involving research, data analysis, and developing models of human cognition. Job prospects are strong in academia, industry, and technology sectors, especially for those skilled in programming, machine learning, and statistical analysis. The field often requires advanced degrees such as a master's or Ph.D. and familiarity with tools like Python, MATLAB, or R.

What kind of jobs can I get with a computational cognitive science degree?

A degree in computational cognitive science prepares individuals for roles such as cognitive scientist, data analyst, machine learning engineer, human factors specialist, or research scientist. These jobs often involve analyzing human behavior, developing AI models, designing user interfaces, or conducting experiments, and typically require skills in programming, statistics, and cognitive modeling.

What are popular job titles related to Computational Cognitive Science jobs in California?

For Computational Cognitive Science jobs in California, the most frequently searched job titles are:

What job categories do people searching Computational Cognitive Science jobs in California look for?

The top searched job categories for Computational Cognitive Science jobs in California are:

What cities in California are hiring for Computational Cognitive Science jobs?

Cities in California with the most Computational Cognitive Science job openings:

Computational Cognitive Science jobs near you
Infographic showing various Computational Cognitive Science job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $64,613 per year, or $31.1 per hour.

Research Scientist - Computational Neuroscience

Jobtailor

Emeryville, CA • On-site

$90 - $130/hr

Other

Posted 5 days ago

Job description

Responsibilities
  • Read, analyze, and synthesize neuroscience, cognitive science, and computational neuroscience literature.
  • Develop biologically plausible computational models of neural circuits, brain regions, and large-scale brain systems.
  • Compare model predictions with experimental data and refine models accordingly.
  • Propose and pursue original research directions that advance our understanding of brain computation.
  • Document research findings and communicate results through technical reports, publications, and presentations.
Requirements
  • Experience programming in Python
  • Familiarity with scientific computing libraries such as Jax, Pytorch, NumPy, SciPy, or similar tools
  • Research experience in systems, computational, and theoretical neuroscience
  • Ability to work independently and communicate technical findings clearly
  • Experience working with data analysis, statistics, or machine learning workflows
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