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Computational Scientist Jobs (NOW HIRING)

UAB

COMPUTATIONAL SCIENTIST (2)

Tampa, FL

$85K - $139K/yr

Our engineers are experienced in design, development, and commercialization of innovative hardware and software systems for the aeronautic and life sciences industry. As one of the nation's leading ...

UAB NOVA RENT

COMPUTATIONAL SCIENTIST (2)

Birmingham, AL · On-site

$85K - $139K/yr

Our engineers are experienced in design, development, and commercialization of innovative hardware and software systems for the aeronautic and life sciences industry. As one of the nation's leading ...

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Computational Scientist information

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$50.5K

$111.3K

$137.5K

How much do computational scientist jobs pay per year?

As of Jul 23, 2026, the average yearly pay for computational scientist in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Computational Scientist position, and why are they important?

To thrive as a Computational Scientist, you need strong analytical skills, advanced knowledge of mathematics and computer science, and typically a graduate degree in a quantitative field such as physics, engineering, or computer science. Familiarity with programming languages like Python, R, or C++, experience with high-performance computing, and tools such as MATLAB or scientific visualization software are vital. Excellent problem-solving abilities, collaboration, and effective communication skills make someone stand out in this position. These skills are crucial for developing models, analyzing complex data, and communicating scientific insights to interdisciplinary teams.

What can you do with a computational science degree?

A computational scientist can work in fields such as data analysis, simulation, modeling, and algorithm development across industries like healthcare, finance, and engineering. They often use programming languages, high-performance computing, and statistical tools to solve complex problems. Career options include research roles, software development, and data science positions requiring strong analytical and technical skills.

What is a Computational Scientist job?

A Computational Scientist uses advanced computing techniques, algorithms, and simulations to solve complex scientific and engineering problems. They work across various fields, such as physics, biology, chemistry, and engineering, developing models and running simulations to analyze large datasets. Their role often involves programming, data analysis, and collaboration with domain experts to gain insights and make predictions.

What is the average salary of a Computational Biologist?

The average salary of a Computational Biologist typically ranges from $70,000 to $110,000 annually, depending on experience, education, and location. Professionals in this field often work with bioinformatics tools and programming languages like Python or R, and advanced degrees can lead to higher compensation.

What is the difference between a computer scientist and a computational scientist?

A computational scientist applies computer science, mathematics, and domain-specific knowledge to solve complex scientific problems using modeling, simulation, and data analysis. In contrast, a computer scientist primarily focuses on developing algorithms, software, and systems, often working in areas like programming, data structures, and theoretical computing. Both roles require strong programming skills, but computational scientists typically work in research environments and use specialized tools for scientific computing.

What does a computational scientist do?

A computational scientist develops and applies mathematical models, algorithms, and simulations to analyze complex scientific problems. They often use programming languages, high-performance computing, and data analysis tools to interpret large datasets and support research across various scientific disciplines.

What does a typical day look like for a Computational Scientist?

A typical day for a Computational Scientist may involve developing and running computer simulations, analyzing large datasets, or creating algorithms to address complex scientific problems. You might spend time coding, troubleshooting computational models, collaborating with researchers or engineers, and documenting your findings. The work often involves both independent problem-solving and teamwork within multidisciplinary groups. Additionally, presenting results, preparing research papers, or contributing to grant proposals could be regular tasks, depending on your specific employer and industry. This dynamic role offers a blend of technical challenges and opportunities for innovation.

More about Computational Scientist jobs
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What are the most commonly searched types of Computational Scientist jobs? The most popular types of Computational Scientist jobs are:
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What states have the most Computational Scientist jobs? States with the most job openings for Computational Scientist jobs include:
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Computational Scientist jobs near you
Infographic showing various Computational Scientist job openings in the United States as of July 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 81% In-person, and 19% Remote job distribution, with an average salary of $111,343 per year, or $53.5 per hour.

Computational Scientist, Structural & Thermal

Periodic Labs

Menlo Park, CA • On-site

Full-time

Posted 22 days ago

Job description

About Periodic Labs
Periodic Labs is an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, semiconductors, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
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 develop structural, thermal, and coupled thermo-mechanical simulation capabilities for semiconductor systems and advanced materials.
This role is for someone who thinks of themselves as both a scientist and a software engineer. You understand solid mechanics and heat transfer at a level that goes beyond configuring a commercial FEA package, and you are comfortable building, extending, or automating solvers when the physics or scale of the problem requires it.
What You'll Do
  • Develop agent-based structural and thermal simulation capabilities for problems central to Periodic Labs' work: wafer stress and warpage, thin-film residual stress, thermo-mechanical reliability, thermal budget modeling, process-induced deformation, fracture and delamination, and coupled heat-stress problems in semiconductor structures.
  • Build or extend custom solvers where commercial FEA tools are too slow, too opaque, or insufficiently flexible. This may include custom FEM implementations, phase-field fracture models, crystal plasticity codes, thin-film mechanics frameworks, or reduced-order mechanical models, written in Python, C++, or Julia.
  • Model materials behavior at the level the physics requires: elasticity, plasticity, viscoelasticity, creep, fracture, diffusion-induced stress, thermal expansion mismatch, interfacial mechanics, and materials evolution under process conditions.
  • Couple structural models to thermal, fluid, or chemical physics as the problem demands.
  • Validate models against experimental measurements including wafer metrology, curvature and bow measurements, DIC, profilometry, nanoindentation, or failure analysis data.
  • Design and curate evaluation datasets in collaboration with RL researchers to train LLMs capable of directing complex simulation pipelines.
  • Generate simulated datasets for ML training in regimes where experimental coverage is expensive or difficult to achieve.
  • Build and automate simulation pipelines at scale. Not just setting up individual runs, but architecting workflows that connect simulation outputs to data infrastructure, ML systems, and autonomous experimentation loops.
  • Integrate mechanics and thermal models into Periodic Labs' AI-driven workflows so that simulations become active tools for process optimization and engineering decision-making.
You Will Thrive Here If You Have
  • Periodic Labs is an early-stage startup, and we're looking for someone who can bring technical leadership to modeling structural and thermal behavior in semiconductor devices, not necessarily someone who already has every skill listed below. A strong growth mindset, demonstrated ownership, and a track record of getting up to speed quickly in new technical areas are much more important than experience in semiconductors.
  • A PhD or equivalent research experience in mechanical engineering, materials science, aerospace engineering, or a closely related field, with a strong foundation in solid mechanics and heat transfer. Strong early-career candidates with a demonstrated upward trajectory are encouraged to apply.
  • Hands-on experience with computational mechanics at the code level: writing or substantially modifying FEM codes, implementing constitutive models, or developing custom solvers for structural or thermal problems.
  • Familiarity with open-source simulation frameworks such as FEniCS, deal.II, MOOSE, or similar is a strong positive signal. Contributions to open-source projects that others actually use are even better.
  • Strong Python skills. Proficiency in C++ is a plus. Experience running simulations programmatically at scale, not just point-and-click.
  • Deep understanding of solid mechanics theory: continuum mechanics, tensor formulations, constitutive modeling, variational methods, and numerical methods for PDEs.
  • Experience using mechanics or thermal simulations to explain experimental observations, guide materials or process decisions, or surface failure mechanisms that were not obvious from measurement alone.
  • Genuine curiosity about AI and a desire to work at the boundary of simulation and machine learning, not because it is required, but because you find it interesting.
Strong Candidates May Also Have
  • Experience with GPU-accelerated FEM, reduced-order mechanical models, surrogate models, or physics-informed neural networks for structural problems.
  • Familiarity with multiscale mechanics: bridging from atomistic or DFT-informed potentials through molecular dynamics, mesoscale methods, and continuum mechanics.
  • Deep expertise in thin-film mechanics: residual stress, Stoney equation regimes and their limits, film-substrate interactions, delamination, and stress evolution during deposition.
  • Experience with wafer-scale mechanics: bow, warp, thermal cycling reliability, packaging-induced stress, or interconnect mechanics in advanced packaging contexts.
  • Background in fracture mechanics or damage modeling: LEFM, cohesive zone models, phase-field fracture, fatigue, or statistical failure models.
  • Knowledge of semiconductor metrology, failure analysis, or process integration that gives physical intuition for how models connect to real manufacturing decisions.
Mechanics:
  • Minimum education: bachelor's degree or an equivalent combination of education and training or experience
  • Location: Our lab is located in Menlo Park and we prefer folks to be located in Menlo Park or San Francisco but can be flexible based on role
  • Compensation: The annual compensation range for this role - $225,000-325,000
  • Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process with our legal support.

We're building a team of the world's best - the scientists, engineers, and problem-solvers who don't just follow the frontier, they define it. If you're driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.

Apply