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Computational Intelligence Jobs (NOW HIRING)

Computational Designer

Los Angeles, CA ยท On-site +1

$75K - $110K/yr

Computational Designers research initiatives and actively contribute to initiatives in the areas of Artificial Intelligence, Machine Learning, and Generative Design as well as other emergent ...

Computational Designer

Dallas, TX ยท On-site +1

$75K - $110K/yr

Computational Designers research initiatives and actively contribute to initiatives in the areas of Artificial Intelligence, Machine Learning, and Generative Design as well as other emergent ...

Computational Designer

Tustin, CA ยท On-site +1

$75K - $110K/yr

Computational Designers research initiatives and actively contribute to initiatives in the areas of Artificial Intelligence, Machine Learning, and Generative Design as well as other emergent ...

Computational Designer

New York, NY ยท On-site

$75K - $225K/yr

Role Overview OXMAN is seeking a Computational Designer to join the EDEN design team and develop procedural design workflows that integrate ecological intelligence into architecture, landscape, and ...

AI Solutions Architect

Menlo Park, CA ยท On-site

$228.94K - $231.60K/yr

... in AI; (7) Computational intelligence and non-convex optimization techniques; (8) Time-series Analysis techniques with Statistics and AI; (9) Applied and mathematics statistics; (10) Cloud ...

$76.70K - $129.50K/yr

POSITION SPECIFICS We are seeking highly motivated Research and Development Engineers to join our Computational Intelligence and Visualization Application Department of the Applied Research ...

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Computational Intelligence information

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$11K

$100.6K

$133K

How much do computational intelligence jobs pay per year?

As of May 31, 2026, the average yearly pay for computational intelligence in the United States is $100,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,500.00 and $132,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Computational Intelligence Specialist, and why are they important?

A Computational Intelligence Specialist typically requires strong expertise in mathematics, programming (often Python or MATLAB), and a solid background in areas like machine learning, neural networks, and evolutionary algorithms, usually supported by a degree in computer science or a related field. Familiarity with technical tools such as TensorFlow, PyTorch, MATLAB, and data processing platforms is essential, along with relevant certifications or specialized coursework. Analytical thinking, creativity, and effective problem-solving abilities help professionals excel in developing innovative solutions and collaborating with multidisciplinary teams. These skills are vital for designing intelligent systems that can tackle complex, real-world problems efficiently and accurately.

What are some common challenges faced by professionals working in Computational Intelligence, and how can they be addressed?

Professionals in Computational Intelligence often encounter challenges such as handling large and complex datasets, ensuring the interpretability of models, and keeping up with rapid advancements in algorithms and technology. Addressing these requires strong collaboration with domain experts, continuous learning through research and professional development, and applying best practices in data management and model validation. Effective teamwork and clear communication are essential, as projects frequently involve cross-functional teams including data scientists, engineers, and stakeholders from various disciplines.

What is computational intelligence?

Computational intelligence is a field of artificial intelligence that focuses on developing algorithms and systems that can learn, adapt, and solve complex problems without explicit human programming. It typically includes techniques such as neural networks, fuzzy systems, evolutionary computation, and swarm intelligence. These methods are inspired by natural processes and are used in various applications like pattern recognition, optimization, and data analysis. Computational intelligence is widely used in industries ranging from finance to robotics.

What is the difference between Computational Intelligence vs Data Scientist?

AspectComputational IntelligenceData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; knowledge of machine learning, neural networksDegree in Statistics, Computer Science, or related fields; expertise in data analysis, programming
Work EnvironmentResearch labs, AI development teams, academiaBusiness environments, analytics teams, tech companies
Industry UsageAI research, pattern recognition, optimization problemsData analysis, predictive modeling, business insights

Computational Intelligence focuses on developing algorithms that mimic human decision-making and problem-solving, often in research or AI development settings. Data Scientists analyze large datasets to extract actionable insights for business decisions. While both roles require programming and analytical skills, Computational Intelligence emphasizes AI algorithm creation, whereas Data Scientists focus on data analysis and visualization.

More about Computational Intelligence jobs
Computational Scientist in the Artificial Intelligence for Science (AIScience)

Computational Scientist in the Artificial Intelligence for Science (AIScience)

Princeton Plasma Physics Laboratory

Princeton, NJ โ€ข On-site

$163.60K - $261.40K/yr

Full-time

Posted 6 days ago


Job description

Overview
The Princeton Plasma Physics Laboratory (PPPL) seeks to fill a Computational Scientist in Artificial Intelligence For Science (AI4Science) position in the Computational Sciences Department. The successful candidate will establish and solicit long-term funding for a program focused on (a) foundational research in Artificial Intelligence and Machine Learning (AI/ML), and (b) application-oriented research in PPPL-relevant AI4Science topics. This is a leadership position that will strongly align with the Genesis Mission - a new initiatives in AI/ML for Science that has been launched by the Department of Energy (DOE). The incumbent will develop a fast-paced AI/ML program strategically aligned with DOE and other Federal Agency goals, ensuring that the research program advances and fits within PPPL Annual Laboratory Plans (ALP) goals.
Artificial Intelligence for Science and Energy represents a fundamental change in the scientific enterprise and an opportunity to provide foundational capabilities upon which to broaden PPPL's mission. The incumbent will build new capabilities in the Computational Sciences Department to leverage this once-in-a-generation opportunity to build an AI4Science research program at PPPL. Specifically, the incumbent will address the emerging need for AI/ML in fusion, other areas of plasma physics, and computational sciences. In addition, the incumbent will work with CSD Leadership to make key hires, build core research capabilities (including training of existing staff), and design a research program to discover new methods in data assimilation, experimental prediction, control systems, and solutions to partial differential equations.
To establish and solicit long-term funding for a program focused on (a) foundational research in Artificial Intelligence and Machine Learning (AI/ML), and (b) application-oriented research in PPPL-relevant AI4Science topics.
The Computational Sciences Department at PPPL was formed to provide a focus for computational physics and engineering. We specialize in algorithms and applied mathematics, data science and learning, high-performance computing, multiscale integrated modeling, and software technology. While our current strengths reflect the traditional focus of the Laboratory on magnetic confinement fusion (MCF), with funding from the Department of Energy's offices of Fusion Energy Sciences and the Advanced Scientific Computing Research, PPPL has always had a broad and healthy research program in areas other than MCF, including developing the theoretical and computational foundations of the dynamics and thermodynamics of naturally occurring plasmas, and more recently, in AI/ML and AI4Science.
The successful candidate will help develop the laboratory's effort in AI/ML and AI4Science, collaborating with CSD leadership and other laboratory divisions. The candidate will help establish partnerships with Princeton University and other DOE National Laboratories. The candidate will assist in recruiting new team members, seek and secure funds to support the laboratory team, and present and publish original research in this general area. The present position comes with steady-state funding for three years.
We are looking for candidates who can build a strong research program in one or more of the following topics:
  1. Machine Learning for Digital Twins, Foundation Models, and surrogates.
  2. Inference tools for interpretive analysis of experimental and simulation data.
  3. Foundational research in Machine Learning for partial differential equations (PDEs).
  4. Innovative algorithmic and methodological approaches to AI-augmented HPC application acceleration.
  5. Advanced systems and software for AI-augmented High-Performance Computing at scale.
  6. Machine-learning-driven control systems control large and complex experiments in real-time,to avoid "dangerous" conditions (disruption avoidance) using feedback systems.
  7. Scalable hybrid AI-HPC workflows using advanced capabilities.

This position requires building close collaboration with CSD Leadership, PPPL experimentists, the PPPL Theory Department, and Princeton University researchers.
A U.S. Department of Energy National Laboratory managed by Princeton University, the Princeton Plasma Physics Laboratory (PPPL) is tackling the world's toughest science and technology challenges using plasma, the fourth state of matter. With more than 70 years of history, PPPL is a leader in the science and engineering behind the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise to advance research in the areas of microelectronics, quantum sensors and devices, and sustainability sciences. Whether it be through science, engineering, technology or professional services, every team member has an opportunity to contribute to our mission and vision. Come join us!
Responsibilities
Core Duties:
  • 50% Delivering on projects (A.I. research).
  • 30% defined research.
  • 20% writing proposal building critical mass.

Qualifications
Education and Experience:
  • Ph.D. in Computer Science, Mathematics, Applied Mathematics, or a related field with core training in foundational & applied aspects of AI/ML.
  • Minimum 15 years of professional experience in an academic, scientific, or R&D environment.
  • A proven track record of publishing original results in peer-reviewed scientific journals.
  • Demonstrated scientific leadership and collaboration experience.

Working Conditions:
  • Day shift, on-site.

Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.
If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.
The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from participation in certain foreign government talent recruitment programs. All PPPL employees are required to disclose any participation in a foreign government talent recruitment program and may be required to withdraw from such programs to remain employed under the DOE Contract.
Standard Weekly Hours
40.00
Eligible for Overtime
No
Benefits Eligible
Yes
Probationary Period
180 days
Essential Services Personnel (see policy for detail)
No
Physical Capacity Exam Required
No
Valid Driver's License Required
No
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Salary Range
$163,600 to $261,400