About this opportunity
University of Texas at Austin lists this Postdoctoral Fellow opportunity in austin, Texas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Job Posting Title:
Postdoctoral Fellow----
Hiring Department:
Department of Marine Science----
Position Open To:
All Applicants----
Weekly Scheduled Hours:
40----
FLSA Status:
Exempt from FLSA----
Earliest Start Date:
Jul 31, 2026----
Position Duration:
Expected to Continue Until Jun 30, 2027----
Location:
AUSTIN, TX----
Job Details:
General Notes
The University of Texas at Austin's Department of Marine Science and the Marine Science Institute, in collaboration with the Department of Computer Science's Computer Vision group, invite applications for an exciting postdoctoral position at the intersection of marine ecology, ocean technology, machine learning, and high-throughput biological imaging.
This position offers a rare opportunity to help pioneer the use of advanced shadowgraph imaging systems for studying the transport and behavior of plankton and larval organisms in dynamic and estuarine environments.
Purpose
The successful candidate will help develop and validate AI-driven pipelines for the detection, segmentation, classification, and tracking of zooplankton and estuarine-dependent larvae in noisy, high-volume imaging datasets collected under challenging field conditions. The work will involve applying state-of-the-art machine learning approaches to classify organisms despite cluttered imagery, marine snow, suspended particles, and subtle morphological differences among taxa.
This position will be located in Austin, TX
Responsibilities
Developing automated image-analysis workflows; implementing visual validation protocols
Exploring active learning and crowdsourced annotation approaches
Quantifying organism movement and behavior through image tracking
Advancing unsupervised and semi-supervised classification methods to discover previously unrecognized biological groupings
Explore adaptive AI-guided imaging strategies, including reinforcement-learning approaches that dynamically optimize sampling based on environmental conditions such as turbidity and currents
Lead the preparation of manuscripts for submission to high-impact peer-reviewed conferences and journals
Contribute to the intellectual development of students and junior researchers
Required Qualifications
PhD in Computer Science or Electrical Engineering received within the last 3 years.
Essential experience includes Python, modern techniques in visual recognition and image segmentation, and the ability to rapidly prototype and fine-tune open-source computer vision models
Preferred Qualifications
Candidates with expertise in computer vision, AI/machine learning, and data science are encouraged to apply.
Salary Range
$70,000
Working Conditions
Most work will take place in a typical office environment
Periodic trips will be made from Austin to the Marine Science Institute in Port Aransas to work with Dr. Sharon Herzka (Department of Marine Science) and other project collaborators. Travel will require driving a personal vehicle.
Required Materials
Resume/CV
3 work references with their contact information; at least one reference should be from a supervisor
Letter of interest
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 thatALLRequired 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 questionspresented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.
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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.
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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.
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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.
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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 . 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.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.