Postdoctoral Fellow

The University of Texas at Austin; Austin (TX); On-site; USD 60,000 - 70,000; Full time

Job summary

An established industry player is seeking a Postdoctoral Fellow to join their innovative research team. This role offers a unique opportunity to engage in cutting-edge research at the Oden Institute, focusing on reinforcement learning and optimal control. The ideal candidate will possess a strong background in deep learning and control theory, and will collaborate with a diverse team to advance scientific knowledge. With a supportive environment for interdisciplinary work, this position promises not only personal growth but also the chance to contribute significantly to impactful research projects. If you're ready to take your career to the next level, this opportunity is for you.

Qualifications

• Ph.D. in mathematics, computer science, or related discipline required.
• Strong hands-on experience in deep learning and control theory.

Responsibilities

• Conduct research in reinforcement learning and optimal control.
• Implement and test algorithms in various computing environments.

Skills

Deep Learning

Control Theory

C/C++ Programming

Scientific Communication

Education

Ph.D. in Mathematics

Ph.D. in Computer Science

Tools

TensorFlow

PyTorch

Julia

JAX

Job description

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General Notes

The Oden Institute is an organized research unit that fosters interdisciplinary programs in computational sciences and engineering, computational medicine, computational geosciences, mathematical modeling, applied mathematics, data science, software engineering, and computational visualization. PhD must have been received within the past three years.

Job Posting Title:

Postdoctoral Fellow

Hiring Department:

Oden Institute

Position Open To:

All Applicants

Weekly Scheduled Hours:

40

FLSA Status:

Exempt

Earliest Start Date:

Immediately

Position Duration:

Expected to Continue Until Sep 30, 2024

Location:

UT MAIN CAMPUS

Job Details:

General Notes

The Oden Institute is an organized research unit that fosters interdisciplinary programs in computational sciences and engineering, computational medicine, computational geosciences, mathematical modeling, applied mathematics, data science, software engineering, and computational visualization. PhD must have been received within the past three years.

The position is funded for a year with possibility of continuation based upon performance review, progress towards research goals, and continuation of funding. The appointment can be renewed up to 4 times, but an overall duration of 2 or 3 years would normally be expected.

Purpose

Postdoctoral research opportunity to collaborate on research in the Oden Institute for Computational Engineering and Sciences under the supervision of Dr. Richard Tsai. Will conduct research in the areas involving reinforcement learning, optimal control, and differential games.

Responsibilities

• Perform basic research in the areas involving vision-based sensor placement and robotic navigation problems and related problems in computer vision, deep learning, and optimal control.
• Implement and test new algorithms in different computing environments.
• Write scientific journal articles describing new findings. Disseminate the research through presentations at scientific conferences, university seminars, and in internal meetings.
  
  
  

Required Qualifications

• Ph.D. in a mathematics, computer science, or a related discipline; earned within the last three years.
• Solid background in control theory, including the Hamilton-Jacobi formulation.
• Strong hands-on experience in deep learning.
• Fluency in C/C++ and Tensorflow, Julia, JAX, or PyTorch.
• Excellent written and oral communication skills.
• Ability to work as part of an interdisciplinary research team.
• Solid publication record.
  
  
  

Preferred Qualifications

• Background in the following areas: computer vision, and optimal control.
• Experience with deep learning and scientific programming; familiarity with Unix/Linux environment.
  
  
  

Salary Range

$60,000 + depending on qualifications.

Working Conditions

• Regular office environment
• May work around standard office conditions.
• Repetitive use of a keyboard at a workstation.
• Travel as required to project meetings or conferences
  
  
  

Required Materials

• Letter of Interest
• Research Statement
• Resume/CV
• Arrange at least three (3) confidential reference letters be sent to Kay Brown ([e-mail])
• Proof of Ph.D. in a mathematics, computer science, or a related discipline earned within the last three years.
  
  
  

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.

Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.

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.

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) [PDF]
• E-Verify Poster (Spanish) [PDF]
• Right To Work Poster (English) [PDF]
• Right To Work Poster (Spanish) [PDF]

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.

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Analyst, and Information Technology

• Industries

  Higher Education

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