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Neural Science Jobs (NOW HIRING)

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest * Distributed computing tools and cloud technology (AWS) QUALIFICATIONS * Degree in Data Science, Computer Science, Engineering, Math ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest * Distributed computing tools and cloud technology (AWS) QUALIFICATIONS * Degree in Data Science, Computer Science, Engineering, Math ...

Waabi

Research Engineer, Neural Rendering

San Francisco, CA · On-site +1

$134K - $235K/yr

You will collaborate with our team of world-renowned scientists and engineers to build innovative ... neural rendering and generative AI to build large-scale, efficient digital twins from real-world ...

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$24K

$104.6K

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How much do neural science jobs pay per year?

As of Jul 10, 2026, the average yearly pay for neural science in the United States is $104,609.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $158,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by neural scientists when conducting research, and how can they be addressed?

Neural scientists often encounter challenges such as securing funding for long-term studies, dealing with complex data analysis, and ensuring ethical treatment of subjects. Collaborating closely with interdisciplinary teams—such as computer scientists, engineers, and clinicians—can help address technical and analytical hurdles. Additionally, staying current with advancements in neuroimaging and data processing tools, and participating in professional networks, can provide valuable support and resources for overcoming these challenges.

Is neuroscience a high paying job?

Neuroscience careers, such as research scientists or clinical neuropsychologists, tend to have moderate to high salaries depending on experience, education, and location. Advanced roles in academia, industry, or healthcare often offer higher compensation, especially for those with specialized skills or advanced degrees like a Ph.D. or M.D.

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

To thrive as a Neural Scientist, you need a deep understanding of neuroscience, biology, and research methodologies, typically supported by an advanced degree (PhD or MD) in a related field. Familiarity with laboratory techniques, neuroimaging tools (like MRI or EEG), and data analysis software such as MATLAB or Python is essential. Critical thinking, problem-solving, and strong communication skills help in interpreting complex data and collaborating with multidisciplinary teams. These skills are crucial for advancing scientific knowledge, conducting impactful research, and effectively sharing discoveries within the field.

What is the difference between Neural Science vs Neuroscience?

AspectNeural ScienceNeuroscience
Required CredentialsBachelor's or Master's in Neuroscience, Psychology, or related fieldsBachelor's or Master's in Neuroscience, Biology, or related fields
Work EnvironmentResearch labs, universities, healthcare settingsResearch institutions, hospitals, academic settings
Industry UsageFocuses on neural mechanisms, brain functions, neural networksBroad study of the nervous system, including neural and behavioral aspects

Neural Science and Neuroscience are closely related fields that often overlap. Neural Science typically emphasizes understanding neural mechanisms and brain functions at a detailed level, often with a focus on neural networks and systems. Neuroscience is a broader discipline that encompasses the study of the entire nervous system, including behavioral and cognitive aspects. Both fields require similar educational backgrounds and are used in research, healthcare, and academia, but Neural Science tends to be more specialized in neural processes.

What is neural science?

Neural science, also known as neuroscience, is the study of the nervous system, including the brain, spinal cord, and networks of neurons. It seeks to understand how these systems function at molecular, cellular, and behavioral levels, and how they control thought, emotion, and behavior. Neural science combines biology, psychology, chemistry, computer science, and other fields to explore how the brain processes information and how neurological disorders can be treated. Careers in neural science can involve research, clinical practice, or technology development related to brain health and cognitive function.

What can you do with a neural science degree?

A neural science degree prepares individuals for careers in research, healthcare, and technology, including roles such as neuroscientist, research scientist, clinical neuropsychologist, or data analyst. It often involves skills in laboratory techniques, data analysis, and understanding neural systems, with opportunities in academia, healthcare institutions, biotech companies, and tech firms working on brain-computer interfaces or AI applications.

What are 5 potential jobs for neurology?

Neural science graduates can pursue careers such as clinical neurologist, neuroscience researcher, neuropsychologist, neuroimaging technician, or neurological surgeon. These roles often require specialized training, certifications, and knowledge of neuroanatomy, neurophysiology, and medical tools like MRI or EEG equipment. Job opportunities are available in hospitals, research institutions, and healthcare facilities.

What kind of careers are in neuroscience?

Careers in neuroscience include roles such as research scientist, clinical neuropsychologist, neuroimaging technician, and pharmaceutical researcher. These positions often require strong backgrounds in biology, psychology, or related fields, along with skills in data analysis, laboratory techniques, and sometimes advanced degrees or certifications.
More about Neural Science jobs
What job categories do people searching Neural Science jobs look for? The top searched job categories for Neural Science jobs are:
Neural Science jobs near you
Senior System Software Engineer - Neural Graphics SDKs

Senior System Software Engineer - Neural Graphics SDKs

Nvidia

Redmond, WA • On-site

$156K - $193K/yr

Full-time

Posted 8 days ago

Job description

NVIDIA is a world-leader in Gaussian Splatting and Neural reconstruction. Our team builds the Omniverse NuRec SDK to enable robotic, healthcare, and AV developers to build better models faster with closed-loop validation and closed-loop training grounded in real-world scenarios.

Do you obsess about software engineering? So do we! We are looking for a strong System Engineer to develop and maintain NVIDIA's software ecosystem for neural graphics, including key OSS platforms like GSplat. Your software will serve a booming community of developers eager to bridge the gap between the real world and simulations. Join our amazing team and help us build the future of Physical AI!

What you'll be doing:

  • Implement, validate, release and maintain SDKs, APIs, libraries for Neural Reconstruction, including key Open Source projects like GSplat.

  • Influence software architecture, validation strategy and technical roadmaps to ensure outstanding usability for our developers across many fields, from research to large-scale production use.

What we need to see:

  • Master's of Science in Computer Science or Electrical engineering or equivalent experience.

  • 5+ years of practical experience.

  • Track record developing and maintaining developer-focused, production-grade software for computer graphics or computer vision (for instance game engines, rendering software).

  • Proficiency with Python and C++.

  • Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization, release).

  • Experience developing high-performance distributed systems (micro-services, Kubernetes).

  • Excellent written, visual, and verbal communication to present architectural challenges, tradeoffs, and alternatives.

  • Curiosity and drive to learn new technologies and partner across teams and functions.

Ways to Stand Out from the Crowd:

  • Strong fundamentals in real-time graphics or other performance-critical domains.

  • Experience in GPU-accelerated software with CUDA, Slang, or other shading languages (GLSL, HLSL, Metal) for low-latency, high-throughput applications.

  • Algorithmic expertise in neural reconstruction (NERFs, Gaussian Splats).

  • History of multidisciplinary creativity and innovation around software engineering in multiple problem domains.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 2, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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