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Computational Cognitive Science Jobs (NOW HIRING)

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 ...

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 ...

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Computational Cognitive Science information

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$36.5K

$65.5K

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How much do computational cognitive science jobs pay per year?

As of Jul 21, 2026, the average yearly pay for computational cognitive science in the United States is $65,470.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $69,500.00 per year, depending on experience, location, and employer.

What jobs can I get with a cog sci degree?

A degree in computational cognitive science prepares individuals for roles such as cognitive scientist, user experience researcher, human factors specialist, data analyst, machine learning engineer, and AI researcher. These jobs often require skills in programming, data analysis, and understanding of human cognition, with employment opportunities in tech companies, research institutions, and healthcare. Certifications in programming languages or data analysis tools can enhance job prospects.

Is Cognitive Science a good career?

A career in cognitive science, including roles like computational cognitive scientist, involves interdisciplinary work combining psychology, neuroscience, and computer science. It offers opportunities in research, data analysis, and developing AI systems, often requiring strong analytical skills and familiarity with programming tools. Job prospects depend on education level and specialization, with growth in areas like artificial intelligence and human-computer interaction.

What are the most common challenges faced by professionals in Computational Cognitive Science roles?

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.

What is a Computational Cognitive Science job?

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 the Computational Cognitive Science position, and why are they important?

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 is a computational cognitive scientist?

A computational cognitive scientist studies how the mind processes information using computational models and simulations. They often work with data analysis, programming languages, and cognitive theories to understand perception, learning, and decision-making. This role typically requires knowledge of psychology, computer science, and mathematics.

What can you do with a computational science degree?

A computational cognitive science degree prepares individuals for roles such as data analyst, research scientist, machine learning engineer, or cognitive modeler. Graduates often work in academia, technology companies, healthcare, or research institutions, utilizing skills in programming, data analysis, and modeling to solve complex problems related to human cognition and artificial intelligence.
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Computational Cognitive Science jobs near you
Infographic showing various Computational Cognitive Science job openings in the United States as of July 2026, with employment types broken down into 4% As Needed, 68% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $65,470 per year, or $31.5 per hour.

Neuroscience PhD (Computational / Active Inference)

Clera

San Francisco, CA • On-site

$150K/yr

Full-time

Posted yesterday

Job description

About the Role
Join a small, fast-moving YC Spring 2026 team building the first wearable designed to read and train emotional intelligence. You'll work at the intersection of computational neuroscience and production machine learning, developing the core inference model that quantifies emotional states - energy, mood, and focus - from a rich stream of audio and biometric signals captured by a consumer wearable device.
This is a founding technical role with real ownership. As the company scales, you are expected to grow into a leadership position within the research and ML org. Prototypes are already on users' wrists, and the team is moving fast.
What You'll Do
  • Design, develop, and iterate on the inference model that quantifies emotional states from wearable sensor data (150+ audio and biometric signals)
  • Bridge cutting-edge neuroscience research and production-grade machine learning - you will function effectively as both a research scientist and an ML engineer
  • Evaluate and deploy models into a real consumer product pipeline
  • Help define the scientific direction and methodology for emotional state quantification as the team and product scale
What We're Looking For
Required
  • PhD in computational neuroscience, cognitive science, active inference, or a closely related field - this is a hard requirement
  • Hands-on experience building and deploying inference models to quantify emotional or physiological states from wearable sensor data
  • Strong ML engineering skills: model development, evaluation, and deployment (Python stack)
  • Familiarity with active inference frameworks and computational neuroscience methods
  • Willingness to work on-site in San Francisco (or London)

Not a fit
  • Wet-lab-only neuroscience backgrounds without computational/ML experience
Compensation & Benefits
  • Salary: ~$150,000 USD (San Francisco) / ~£75,000 GBP (London)
  • Equity: Up to 1-2% (founding-level ownership)
  • Backed by angels and strategic partners (pre-Series A / seed stage)
  • Visa sponsorship: Not available - visa transfers are acceptable; otherwise the London office is an option
Location
  • Primary: San Francisco, CA, USA (on-site preferred)
  • Alternative: London, UK (on-site)
  • Location is flexible between these two offices

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