Research Engineering/ Scientist Associate II – Computational Research

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. 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 questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above. ---- Employment Eligibility: Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval. ---- Retirement Plan Eligibility: The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. ---- Background Checks: A criminal history background check will be required for finalist(s) under considerati