Postdoctoral Fellow

About the role

• 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.

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

Additional information

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.

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.

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.