Research Engineering/ Scientist Associate II – Computational Research

University of Texas; Austin, Northern (TX, KY); Hybrid; USD 41,000 - 50,000; Full time

Job summary

The University of Texas at Austin Savinov lab seeks a Research Engineering/ Scientist Associate II – Computational Research to contribute to projects designing protein fragments as universal regulators of protein interactions. You will set up and perform computational predictions and train new lab members in these techniques, while maintaining computational infrastructure.

Applicants should have a Master’s degree (or Bachelor’s with 2+ years) and hands-on experience with Python, BASH, HPC, AI/ML

Qualifications

• Master’s degree in a related field or bachelor’s degree plus at least two years of relevant experience.
• Experience with Python, BASH, and high-performance computing environments.
• Experience with AlphaFold and related AI/ML structure-prediction approaches.
• Experience with data science and large experimental/computational datasets.
• Experience with AI development tools.
• Ability to learn new computational/AI techniques and maintain detailed records.
• Strong organizational and communication skills.

Responsibilities

• Computational research and research support to discover and design protein fragments as regulators of cellular protein interactions.
• Maintain the lab’s computational infrastructure and assist with training new lab members in computational methods.

Skills

Python

BASH

HPC

AI/ML tools

AlphaFold

Data science

Teamwork

Education

Master's degree

Bachelor's degree + 2 yrs experience

Tools

GitHub

Shared HPC infra

Job description

## Research Engineering/ Scientist Associate II – Computational ResearchApply: AUSTIN, TX: Full time: Posted Yesterday: R\\_00048941**Job Posting Title:**Research Engineering/ Scientist Associate II – Computational Research**----****Hiring Department:**Molecular Biosciences**----****Position Open To:**All Applicants**----****Weekly Scheduled Hours:**40**----****FLSA Status:**Exempt from FLSA**----****Earliest Start Date:**Immediately**----****Position Duration:**Expected to Continue Until Sep 17, 2027**----****Location:**AUSTIN, TX**----****Job Details:****Purpose**The Savinov lab at UT Austin (https://www.savinovlab.com/) is pursuing multiple projects centered around discovering and designing protein fragments as universal regulators of protein interactions in health and disease – including in the contexts of antibiotic resistance, cell migration, neurodegeneration, and cancer. The lab seeks a highly motivated, curious, and organized individual to join the team and contribute to multiple research projects, working both individually and as part of a group. The candidate will set up and perform computational predictions and develop novel computational approaches supporting research efforts in the lab, and also be involved in training new lab members in these techniques. Computational approaches will include AI/ML approaches, protein design methods, bioinformatics, and data science methods to handle large experimental and computational datasets. The candidate should have experience with working on high-performance computing systems. Additional experience in experimental biology is favorable, but not required.**Responsibilities*** Computational research and research support. Support and perform computational research to discover and design protein fragments as regulators of cellular protein interactions, both individually under the guidance of the PI and as part of a group. Computational approaches will include AI/ML-based structure prediction, protein design, and bioinformatics approaches, as well as data science to handle and extract insights from large experimental datasets. Perform routine computational experiments and develop novel approaches to address research problems. Maintain the lab’s computational infrastructure. Maintain careful records.* Training and general lab support. Assist with maintaining shared resources, protocols and documentation; help train new laboratory members computational methods; assist with additional research and operational needs as appropriate.## Required Qualifications* Master’s degree in a related field, or bachelor’s degree plus at least two years of relevant experience.* Experience with and willingness to perform routine and novel computational methods, including on high-performance computing environments.* Experience with AlphaFold and related AI/ML structure-prediction approaches.* Experience with Python, BASH, and high-performance computing systems.* Experience with data science and working with large experimental and computational datasets.* Experience with AI dev tools. Experience with learning new computational and AI/ML techniques and a strong desire to continue to do so.* Demonstrated reliability, attention to detail, and ability to maintain accurate records and follow established procedures.* Ability to work both independently and as part of a group, and recognize and respond to problems in a timely manner. Strong organizational and communication skills.## Preferred Qualifications* Experience with managing shared codebases via GitHub is desirable.* Experience with setting up and managing shared computational infrastructure.* Additional experience with experimental biology.## Salary Range$45,000+ depending on qualifications## Working Conditions* Uniforms and/or personal protection equipment (furnished).* May work around chemical fumes.* May work around standard office conditions.* May work around biohazards.* May work around chemicals.## 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. Once your job application has been submitted, you cannot make changes.