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Computational Engineering Jobs in Austin, TX (NOW HIRING)

Prepare and optimize CAD models for computational analysis, conduct multidisciplinary simulations, and develop automated analysis workflows to improve engineering efficiency. * Support aerodynamic ...

Prepare and optimize CAD models for computational analysis, conduct multidisciplinary simulations, and develop automated analysis workflows to improve engineering efficiency. * Support aerodynamic ...

Aerodynamics Engineer

Austin, TX · On-site

$120 - $170/hr

Prepare and optimize CAD models for computational analysis, conduct multidisciplinary simulations, and develop automated analysis workflows to improve engineering efficiency. * Support aerodynamic ...

Cadence is a market leader in AI and digital twins, pioneering the application of computational software to accelerate innovation in the engineering design of silicon to systems. Founded in 1988, the ...

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Computational Engineering information

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How much do computational engineering jobs pay per year?

As of Aug 20, 2026, the average yearly pay for computational engineering in Austin, TX is $120,447.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $130,300.00 per year, depending on experience, location, and employer.

What is a computational engineer?

A Computational Engineering job involves using mathematical models, algorithms, and computer simulations to analyze and solve engineering problems. It combines principles from computer science, applied mathematics, and engineering to improve product design, optimize systems, and enhance efficiency in various industries. Professionals in this field develop software tools, conduct simulations, and utilize high-performance computing to solve complex engineering challenges in areas such as aerospace, automotive, energy, and healthcare.

What skills and qualifications are needed to thrive as a computational engineer?

To thrive as a Computational Engineer, a strong background in mathematics, computer science, and engineering fundamentals is essential, generally supported by a degree in computational engineering or a related field. Familiarity with programming languages like Python, MATLAB, or C++, as well as experience using simulation software and high-performance computing systems, is typically required. Analytical thinking, effective communication, and problem-solving abilities are important soft skills for collaboration and innovation. These competencies enable Computational Engineers to develop accurate models, optimize complex systems, and deliver efficient solutions in multidisciplinary environments.

What are some common challenges computational engineers face in their work?

Computational Engineers often encounter complex, large-scale problems that require developing accurate and efficient computational models, which can be challenging due to intricacies in physical systems or computational resource limitations. Managing tight project deadlines while ensuring high-quality results and adapting to rapidly evolving technology are also common aspects of the role. Collaboration across multidisciplinary teams—often with scientists, designers, or other engineers—requires strong communication and adaptability. Embracing these challenges can help Computational Engineers expand their expertise and positively impact project outcomes.

Is computational engineering in demand?

Computational engineering is in high demand across industries such as aerospace, automotive, and energy, as it involves using advanced modeling, simulation, and programming skills to solve complex engineering problems. The field offers strong job growth prospects, especially for those proficient in programming languages, numerical methods, and software tools like MATLAB or Python.

What does a computational engineer do?

A computational engineer develops and applies mathematical models, algorithms, and simulations to solve complex engineering problems. They often use programming languages and software tools to analyze data, optimize systems, and improve designs across various engineering disciplines.

What are the most commonly searched types of Computational Engineering jobs in Austin, TX?

The most popular types of Computational Engineering jobs in Austin, TX are:

What job categories do people searching Computational Engineering jobs in Austin, TX look for?

The top searched job categories for Computational Engineering jobs in Austin, TX are:

What cities near Austin, TX are hiring for Computational Engineering jobs?

Cities near Austin, TX with the most Computational Engineering job openings:

Infographic showing various Computational Engineering job openings in Austin, TX as of August 2026, with employment types broken down into 6% Internship, 69% Full Time, 8% Part Time, 10% Temporary, and 7% Contract. Highlights an 85% In-person, 7% Hybrid, and 8% Remote job distribution, with an average salary of $120,447 per year, or $57.9 per hour.

Postdoctoral Fellow - Computational Affective and Social Cognition Lab

The University of Texas at Austin

Austin, TX • On-site

$70K/yr

Full-time

Re-posted 6 days ago


University Of Texas at Austin rating

8.3

Company rating: 8.3 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

126th of 620 rated colleges and universities


Job description

Job Posting Title:
Postdoctoral Fellow - Computational Affective and Social Cognition Lab
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Hiring Department:
Department of Psychology
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Position Open To:
All Applicants
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Weekly Scheduled Hours:
40
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FLSA Status:
Exempt from FLSA
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Earliest Start Date:
Immediately
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Position Duration:
Expected to Continue Until May 31, 2030
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Location:
UT MAIN CAMPUS
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Job Details:
General
The CASCog Lab, an interdisciplinary lab at the intersection of Psychology and Artificial Intelligence, is housed in the Department of Psychology, in the College of Liberal Arts at The University of Texas at Austin. In our lab, we are interested in studying how people and machines understand emotions. Recent projects include: how generative AI may be able to provide empathy, how people perceive such artificial empathy, and how this relates to AI sycophancy and mental health. For more information about the research conducted in the lab, please visit the lab website at https://cascoglab.psy.utexas.edu/, or Prof. Ong's website at https://cascoglab.psy.utexas.edu/desmond. This position is a for a fixed-term of one year.
Purpose
The Computational Affective and Social Cognition Lab (CASCogLab) in the Department of Psychology at The University of Texas at Austin, directed by Professor Desmond Ong, is hiring a full-time Postdoctoral Research Fellow for academic year 2026-27.
Responsibilities
The Postdoctoral Fellow will work primarily on an NSF-funded project related to studying how well AI models understand human emotions. The scope includes questions like: how do machines reason about human emotions in context, over time, and appropriately reason over interventions (e.g., emotion regulation). The Postdoctoral Fellow will also be invited to contribute to other ongoing and related projects in the lab: characterizing the advantages and disadvantages of artificial empathy; studying the implications for mental health; studying the implications for development (e.g., adolescents); developing technical solutions for mitigating some harmful AI behaviors (like AI sycophancy); contributing to mental health and other safety-relevant benchmarks; policy-relevant activities.
The Postdoctoral Research Fellows will work closely with the Principal Investigator, Prof. Ong, on all stages of the research process: from conducting literature reviews, designing and running empirical studies including both experiments with humans as well as with machines (via simulations etc), to data analysis and computational modeling of the data, to writing up the results for publication and presentation. The Postdoctoral Research Fellow will propose and lead research projects of their own under the supervision of the Principal Investigator. Finally, the postdoctoral research fellows will contribute to grant writing and aspects of grant management as part of their training.
Duties
  • Leading research projects and handling all aspects of the research process, including: handling ethics review and compliance; recruiting participants for empirical studies; designing and implementing simulation studies involving AI models; managing and analyzing data; managing code bases; and supervising undergraduate research assistants
  • Writing up research into manuscripts, and presenting research at conferences.
  • Grantsmanship, including applying for training fellowships or assisting with larger grant applications.
  • Other duties as assigned.

Requirements
Ph.D. in Psychology, Cognitive Science, Computer Science, or a related field received no more than three years prior to the start date. Substantial research experience and research-relevant skills, including:
  • Experience conducting psychological experiments: designing and constructing experiments, recruiting and consenting participants, and collecting data.
  • Statistical skills, including data analysis and visualization.
  • Familiarity with programming, including programming skills in R and/or Python.

Preferred Qualifications
  • Experience with or willingness to learn using LLMs for psychological research.
  • Experience with or willingness to learn open science practices in psychology (e.g.,version control on Github, reproducible analysis reports in RMarkdown, pre-registration).
  • Demonstrated self-motivation, accountability, detail-oriented, excellent time management skills.
  • Clear communication skills and ability to work in a team.
  • Positive and enthusiastic attitude towards learning

Salary
$70,000
Required Materials
  • A Cover Letter (not more than 3 pages) stating your research interests and long-term goals. Please also discuss how your research interests, prior research experience, and statistical and computational skills, aligns with that of the lab.
  • A Curriculum Vitae
  • Up to 2 representative publications
  • The names, affiliations, and contact information of three individuals who will be willing to provide a recommendation letter describing your research experience and character.

Employment Eligibility:
Please make sure you meet all the required qualifications and you can perform all of the essential functions with or without a reasonable accommodation.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
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E-Verify:
The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university's company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
  • E-Verify Poster (English and Spanish) [PDF]
  • Right to Work Poster (English) [PDF]
  • Right to Work Poster (Spanish) [PDF]

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Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.

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