Research Assistant

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Job Details:

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, artificial intelligence, software engineering, and computational visualization.

The University of Texas at Austin is a nationally ranked, tier-one research institution and one of the largest employers in central Texas. UT is located in the heart of Austin, a vibrant city that frequently appears on lists of best cities to live and work. Committed to recruiting and retaining a talented workforce, the university offers competitive salaries and benefits, an extensive support network, and above all, an enriching and highly collaborative community that is deeply passionate about our vision for higher education and public service.

UT Austin offers a competitive benefits package that includes:

• 100% employer-paid basic medical coverage

• Retirement contributions

• Paid vacation and sick time

• Paid holidays

Please visit our Human Resources (HR) website to learn more about the total benefits offered

A Research Assistant role with a focus on preparation and execution of ultra-large protein structure modeling runs and customization of DeepLearning- and Physics-based molecular structure prediction tools to enable modeling on this scale.

This is a part-time position (50% FTE; 20 scheduled weekly hours) with an anticipated end date of December 31, 2026.

• Model Execution & Pipeline Optimization: Prepare, scale, and execute ultra-large protein structure modeling workflows for massive systems (>8000 residues). Adapt, optimize, and troubleshoot existing deep learning and physics-based pipelines to handle extreme scale without memory or performance bottlenecks.

• Tool Customization & Finetuning: Finetune and customize cutting-edge protein structure prediction models (like Boltz, AlphaFold3, etc.). Implement custom scripting to bridge physics-based and machine-learning methodologies.

• Data Management & Analysis: Featurize structural data, manage large datasets, and analyze structural modeling outputs for quality and biological relevance. Maintain rigorous documentation of code, workflows, and benchmarking results.

• Collaborative Support: Assist team members with computational setups, software dependencies, and cluster/cloud environment configurations.

• Education: Bachelor's degree in Computational Biology, Computer Science, Bioinformatics, or a related quantitative/scientific field.

• Experience with featurizing and performing structure modeling for ultra-large protein systems (>8000 residues).

• Experience with training and fine tuning of protein structure prediction models such as Boltz and AlphaFold3.

• Confident scripting skills (Python, Bash).

• Familiarity with deep learning frameworks (PyTorch, PyTorch Lightning).

• Relevant education and experience may be substituted as appropriate.

• Experience with modeling protein interactions using Physics-based approaches (ClusPro, Rosetta, etc.).

• Experience working in High-Performance Computing (HPC) environments (Slurm, CUDA execution) or cloud infrastructure (AWS/GCP) optimized for multi-GPU training.

• Familiarity with containerization tools (Docker, Singularity) for reproducible workflows.

$3,000 monthly. Part-time, 50% FTE (20 Scheduled Weekly Hours)

• May work around standard office conditions

• Repetitive use of a keyboard at a workstation

• Occasional weekend, overtime and evening work to meet deadlines

• Resume/CV

• 3 work references with their contact information; at least one reference should be from a supervisor.

• Letter of interest

Importantfor 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:

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Retirement Plan Eligibility:

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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 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.