Research Assistant

## Research Assistant Apply locations:
UT MAIN CAMPUS time type:
Part time posted on:
Posted Todaytime left to apply:
End Date:
July 23, 2026 (6 days left to apply) job requisition :
R
** Job Posting

Title:

** Research Assistant**---
- **** Hiring Department:
** Oden Institute**---
- **** Position Open To:
** All Applicants**---
- **** Weekly Scheduled

Hours:

** 20**---
- **** FLSA Status:
** Non-Exempt from FLSA**---
- **** Earliest

Start Date:

** Jul 28, 2026**---
- **** Position Duration:
** Expected to Continue Until Dec 31, 2026**---
- ***
* 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, 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## PurposeA Research Assistant role with a focus on preparation and execution of ultra-large protein structure modeling runs and customization of Deep Learning- 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.## Responsibilities
* 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 & Fine tuning:
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.##

Required Qualifications

* 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 Alpha Fold
3.
* Confident scripting skills (Python, Bash).
* Familiarity with deep learning frameworks (PyTorch, PyTorch Lightning).
* Relevant education and experience may be substituted as appropriate.##

Preferred Qualifications
* Experience with modeling protein interactions using Physics-based approaches (Clus Pro, 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.## Salary Range $3,000 monthly. Part-time, 50% FTE (20 Scheduled Weekly Hours)## Working Conditions
* May work around standard office conditions
* Repetitive use of a keyboard at a workstation
* Occasional weekend, overtime and evening work to meet deadlines## 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 that ALL Required Materials have been uploaded.  

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