Research Assistant

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 Purpose 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. 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 & 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. 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 AlphaFold3. 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 (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. Benefits 100% employer-paid basic medical coverage Retirement contributions Paid vacation and sick time Paid holidays 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 #J-18808-Ljbffr