Research Engineering​/Scientist Assitant - Computational Biology and Protein Modeling

Research Engineering/ Scientist Assitant - Computational Biology and Protein Modeling

Oden Institute

All Applicants

20

To Be Determined at Offer

Ongoing

Limited Duration Based on Business Need

UT MAIN CAMPUS

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. UTis located in the heart of Austin, a vibrant city that frequently appears onlists of best cities to live and work. Committed to recruiting and retaining a varied and 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.

• 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.

NOTE:

This position is initially appointed for a six-month term. Continuation beyond the initial six-month assignment is contingent upon funding availability and satisfactory performance.

We are inviting highly motivated individual to join our research group at the Oden Institute, University of Texas s opportunity is designed for individuals with a strong background in biochemistry, molecular biology, biophysics, or a related field who are interested in applying computational methods to problems in protein structure, molecular interactions, and drug discovery.

• Applying protein docking and structure-prediction methods to biologically relevant systems
• Preparing protein, peptide, antibody, and small-molecule structures for computational experiments
• Running, organizing, and analyzing large-scale computational studies
  
  Comparing predictions produced by different docking and structure-prediction tools
• Evaluating protein interfaces, binding modes, structural quality, and biological plausibility
• Working with structural and biological databases such as the Protein Data Bank, Uni Prot, Pfam, Inter Pro, and related resources
• Using tools such as PyMOL, ChimeraX, BLAST, Foldseek, and molecular modeling or docking software
• Designing computational experiments and selecting appropriate controls, benchmarks, and evaluation metrics
• Interpreting computational results in the context of known biochemical and experimental data

• Preparing figures, structural visualizations, reports, and presentations

• Collaborating with machine-learning researchers to identify model limitations and guide further development
• Working with experimental collaborators to propose testable hypotheses and prioritize computational predictions for validation

• Bachelor's Degree in a relevant or related field
• A strong background in biochemistry, molecular biology, structural biology, biophysics, bioinformatics, or a related discipline
• A solid understanding of protein structure and function, including:
  • Amino acid properties and protein folding
  • Protein domains and conformational changes
  • Protein-protein and protein-ligand interactions
  • Noncovalent interactions, binding interfaces, and molecular recognition
• Experience using PyMOL, ChimeraX, or similar molecular visualization software
• Familiarity with biological and structural databases
• Ability to analyze scientific literature and connect computational predictions with biological mechanisms
• Basic scripting or programming experience, preferably in Python
• Comfort working in Linux environments and running computational tools from the command line
• Strong organizational skills and the ability to manage multiple computational experiments and datasets
• Careful attention to structural quality, data interpretation, and reproducibility

Relevant education and experience may be substituted as appropriate.

• Prior experience with protein docking, molecular dynamics, structural alignment, virtual screening,…