ZipRecruiter

Log In

1

Stochastic Partial Differential Equations Jobs (NOW HIRING)

Root Access, Inc.

Machine Learning Engineer

Manhattan, NY · On-site

$150 - $200/hr

Exceptional understanding of partial differential equations (PDEs), vector calculus, automatic differentiation (autograd), and numerical optimization algorithms (Adam, L‑BFGS). * Data Pipelines:

Varsity Tutors

Applied Mathematics Tutor

Laurel, MD · Remote

$18 - $40/hr

Deep knowledge of differential equations, numerical methods, linear algebra applications, optimization, mathematical modeling, Fourier analysis, partial differential equations, and complex analysis.

next page

Showing results 1-20

All JobsStochastic Partial Differential Equations Jobs

Stochastic Partial Differential Equations information

See salary details

$11K

$115.3K

$250K

How much do stochastic partial differential equations jobs pay per year?

As of Sep 9, 2026, the average yearly pay for stochastic partial differential equations in the United States is $115,291.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,000.00 and $250,000.00 per year, depending on experience, location, and employer.

What are stochastic partial differential equations?

Stochastic Partial Differential Equations (SPDEs) are mathematical equations that describe systems evolving over space and time under the influence of random noise. They extend traditional partial differential equations by incorporating stochastic processes, such as Brownian motion, to model uncertainty or randomness in real-world phenomena. SPDEs are widely used in fields like physics, finance, biology, and engineering to simulate complex systems where both spatial interactions and random effects play a crucial role. Solving SPDEs often requires advanced mathematical techniques and computational methods.

What are some common challenges faced by professionals working with stochastic partial differential equations?

Professionals working with SPDEs often encounter challenges related to the complexity of both the mathematical theory and computational implementation. Accurately modeling random phenomena in fields like physics or finance requires a strong grasp of probability, functional analysis, and numerical methods. Additionally, finding efficient and stable algorithms for simulating SPDEs can be demanding, as these equations frequently involve high-dimensional data and require significant computational resources. Collaborating with interdisciplinary teams—such as applied mathematicians, engineers, or domain scientists—is also common, as solutions usually benefit from a blend of theoretical and practical expertise.

What are the key skills and qualifications needed to thrive as a stochastic partial differential equations researcher, and why are they important?

To thrive as an SPDE Researcher, you need a strong background in advanced mathematics, particularly probability theory, functional analysis, and differential equations, typically backed by a PhD in mathematics or a related field. Familiarity with programming languages such as Python or MATLAB, as well as mathematical software like Mathematica or MATLAB, is essential for simulations and computational work. Analytical thinking, problem-solving ability, and effective scientific communication are crucial soft skills for collaboration and dissemination of research. These competencies enable rigorous analysis, efficient modeling, and meaningful contributions to the field of stochastic processes in both academic and applied contexts.

What is the difference between Stochastic Partial Differential Equations vs Data Scientist?

AspectStochastic Partial Differential EquationsData Scientist
Required credentialsAdvanced mathematics, PhD often preferredStatistics, computer science, or related degree
Work environmentResearch labs, academia, specialized industriesTech companies, finance, consulting
Industry usageModeling complex systems with randomnessData analysis, predictive modeling

Stochastic Partial Differential Equations focus on mathematical modeling of systems with randomness, often requiring advanced degrees. Data Scientists analyze data to extract insights, typically working in more applied settings. While both roles involve quantitative skills, their applications and environments differ significantly.

What other helpful pages are available for Stochastic Partial Differential Equations?

Other pages related to Stochastic Partial Differential Equations:

Infographic showing various Stochastic Partial Differential Equations job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $115,291 per year, or $55.4 per hour.

Research Associate in Mechanical and Aerospace Engineering

Charlottesville, VA • On-site

University of Virginia
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about University of Virginiaexternal

$47K - $90K/yr

Full-time

Re-posted 12 days ago

University Of Virginia rating

7.9

Company rating: 7.9 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

213th of 633 rated colleges and universities

Job description

The Computational Fluid Dynamics (CFD) and Propulsion Laboratory in the Department of Mechanical and Aerospace Engineering at University of Virginia is seeking a qualified candidate for a Postdoctoral Research Associate position.
Research in the laboratory focuses on high-performance computing (HPC) methods in CFD, advanced algorithm development, data assimilation and scientific machine learning. The successful candidate will contribute to the development of advanced numerical algorithms for large-scale CFD modeling and simulations, including scalable solvers, domain decomposition methods, and data-driven and physics-driven learning techniques.
The Postdoctoral Research Associate will work as an algorithm developer within the CFD and Propulsion Laboratory and will be responsible for the development, implementation, and analysis of efficient numerical methods for next-generation CFD applications on HPC platforms.
Qualification Requirements
By the start date, applicants must have earned a PhD in Mathematics or Statistics or other related field, and be within 5 years post-PhD. Candidates should demonstrate research experience in a few of the following areas:
  • CFD methods, numerical methods and analysis, stability analysis
  • Scalable solvers, and domain decomposition methods
  • C++ programming, parallel programming, GPU programming
  • Stochastic partial differential equations (PDEs), stochastic processes and analysis
  • Model reduction, surrogate model development
  • Uncertainty quantification

Preferred Qualifications
Preference will be given to candidates with additional expertise in:
  • AI/ML
  • Supercomputing
  • Large-scale computational infrastructure and workflows
  • Peer-reviewed publications in computational mathematics and/or computational/numerical methods

Salary
The anticipated hiring base salary is $53,000.
Application Procedure
Apply online through the UVA Job Board and search for position number R0083690.
Applicants should upload:
  • A cover letter
  • Curriculum vitae
  • Contact information for three professional references

Please note that multiple documents may be uploaded in the application portal.
Application Deadline
Review of applications will begin on June 2, 2026; however, the position will remain open until filled. The University will perform background checks on all new hires prior to employment.
This is a one-year appointment. Renewal is contingent upon available funding and satisfactory performance.
Estimated salary range is $47,500 - $90,000, commensurate with experience.
Questions regarding this position should be directed to Professor Xinfeng Gao at gao@virginia.edu .
For questions about the application process, please contact Richard Haverstrom, Academic Recruiter, at rkh6j@virginia.edu .
For more information on the benefits available to Research Associate at UVA, visit hr.virginia.edu/benefits.
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .

What University Of Virginia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

University of Virginia logo

About University of Virginia

Sourced by ZipRecruiter

The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Charlottesville, VA, US

Year founded

1819

View All University of Virginia Jobs

Apply