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Phd Computational Science Jobs (NOW HIRING)

Accenture

AI/ML Computational Science Engineer

Chicago, IL · On-site

$26.39 - $77.88/hr

You Are As an AI/ML Computational Scientist, you will design, build, and operationalize artificial ... MS or PhD in related field preferred (computer science, engineering, etc.) Compensation at ...

Accenture

AI/ML Computational Science Engineer

Chicago, IL · On-site

$26.39 - $77.88/hr

You Are As an AI/ML Computational Scientist, you will design, build, and operationalize artificial ... MS or PhD in related field preferred (computer science, engineering, etc.) Compensation at ...

Accenture

AI/ML Computational Science Engineer

Chicago, IL · On-site

$26.39 - $77.88/hr

You Are As an AI/ML Computational Scientist, you will design, build, and operationalize artificial ... MS or PhD in related field preferred (computer science, engineering, etc.) Compensation at ...

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How much do phd computational science jobs pay per year?

As of Sep 11, 2026, the average yearly pay for phd computational science in the United States is $83,109.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,500.00 and $93,500.00 per year, depending on experience, location, and employer.

What is a PhD in Computational Science?

A PhD in Computational Science is an advanced research degree focused on the development and application of computational techniques to solve complex problems in science, engineering, and other fields. Students in this program conduct original research involving mathematical modeling, computer simulations, and data analysis. The degree prepares graduates for careers in academia, industry, and government, where they apply computational methods to advance scientific discovery and innovation.

What are the typical collaborative opportunities for a PhD in Computational Science within interdisciplinary research teams?

PhDs in Computational Science often work closely with experts from diverse fields such as biology, engineering, physics, and data science. Collaboration is a key part of the role, as computational scientists provide advanced modeling, simulation, and data analysis expertise that supports the research goals of the team. These professionals regularly participate in joint project meetings, contribute to cross-disciplinary publications, and work with both academic and industry partners. This collaborative environment not only enhances problem-solving but also provides valuable networking and learning opportunities, which can contribute to career growth and innovative research outcomes.

What are the key skills and qualifications needed to thrive as a PhD in Computational Science, and why are they important?

To thrive as a PhD in Computational Science, you need advanced expertise in mathematics, computer science, and domain-specific scientific knowledge, along with a doctoral degree in a related field. Proficiency in programming languages (such as Python, C++, or MATLAB), experience with high-performance computing, and familiarity with simulation or modeling software are typically required. Strong analytical thinking, problem-solving, and the ability to communicate complex concepts clearly are essential soft skills. These competencies are crucial for developing innovative computational solutions to scientific problems and advancing research in multidisciplinary environments.

What is the difference between Phd Computational Science vs Data Scientist?

AspectPhd Computational ScienceData Scientist
Required CredentialsPhD in Computational Science, strong programming, mathematical skillsTypically a bachelor's or master's in data science, computer science, or related fields; some roles prefer a PhD
Work EnvironmentResearch labs, academia, R&D departments in industryCorporate, tech companies, finance, healthcare, often collaborative teams
Industry UsageResearch institutions, universities, specialized R&D sectorsBusiness analytics, product development, machine learning applications

While both roles require strong analytical and programming skills, a Phd Computational Science focuses more on research, modeling, and simulation, often within academic or R&D settings. Data Scientists typically work on data analysis, predictive modeling, and business insights in industry environments. The choice depends on whether you prefer research-oriented work or applied data analysis in a commercial setting.

Is a PhD in computational science worth it?

A PhD in computational science prepares individuals for research, academia, and specialized industry roles that require advanced analytical and programming skills. It can lead to higher-level positions and increased earning potential but involves significant time and financial investment. The value depends on career goals and the demand for expertise in computational methods within specific fields.

What can I do with a PhD in computational science?

A PhD in computational science prepares individuals for research and development roles in academia, industry, and government, focusing on modeling, simulation, and data analysis. Graduates often work as computational scientists, data scientists, software developers, or research scientists, utilizing programming skills and advanced analytical tools to solve complex problems across fields like physics, biology, finance, and engineering.

What are popular job titles related to Phd Computational Science jobs?

For Phd Computational Science jobs, the most frequently searched job titles are:

Infographic showing various Phd Computational Science job openings in the United States as of September 2026, with employment types broken down into 2% Internship, 1% As Needed, 75% Full Time, 20% Part Time, and 2% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $83,109 per year, or $40 per hour.

Computational Scientist, Differentiable Physics

Menlo Park, CA • On-site

Periodic Labs
See more jobs at Periodic Labsexternal

$250K - $350K/yr

Full-time

Posted 6 days ago

Job description

About the Role
Periodic Labs is building AI systems that can simulate physical science, verify predictions, and train on the full scientific method. We are looking for a Computational Scientist to build differentiable, accelerator-ready simulations for industrially relevant continuum-physics problems.
You should be equally comfortable with governing equations, solver code, and deep learning. We are open to expertise in any area of continuum-physics, with at least some experience in fluid dynamics. You will work on building simulation capabilities in challenging, data-limited domains requiring a mix of physics-based and empirical approaches.
What You'll Do
  • Build and extend differentiable solvers for continuum simulation (including but not limited to fluid dynamics), especially multi-scale and multi-physics problems.
  • Implement numerical methods from equations and papers, and diagnose convergence, stability, and modeling failures.
  • Combine simulation with deep learning for surrogate modeling, learned physics, inverse problems, parameter estimation, and optimization.
  • Use automatic differentiation and modern accelerators with JAX or PyTorch to make simulations scalable and trainable.
  • Validate models against experiments, trusted benchmarks, or high-fidelity simulations.
  • Create datasets and evaluations to guide the development of LLMs to accelerate and automate these tasks.
You Will Thrive Here If You Have
  • A PhD or equivalent research experience in applied mathematics, computational science, physics, engineering, computer science, or a related field.
  • Code-level experience building or substantially modifying PDE solvers, numerical methods, or differentiable simulations.
  • Deep expertise in at least one continuum domain, with breadth across domains or a demonstrated ability to learn new physics quickly.
  • Meaningful experience building, training, and evaluating deep-learning models for physical systems.
  • Strong Python and software-engineering skills, especially JAX, PyTorch, Julia, or C++.
  • Experience applying simulation to realistic scientific or engineering problems, not only clean academic benchmarks.
  • A startup mentality: ownership, good judgment under uncertainty, and enthusiasm for building from scratch.
Strong Candidates May Also Have
  • Experience with fluid dynamics plus another continuum domain, or with multiphysics and multiscale modeling.
  • Expertise in adjoint methods, implicit differentiation, differentiable programming, or scientific optimization.
  • Experience accelerating scientific software on GPUs or TPUs.
  • Contributions to scientific open-source software used by others.
  • Experience connecting simulation to experiments, engineering decisions, semiconductors, or autonomous workflows.
Mechanics
  • Minimum education: Bachelor's degree or similar experience
  • Location: Menlo Park, CA (Soon: San Francisco, too)
  • Compensation: $250,000-350,000 + equity
  • Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process.

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