Research Engineering/ Scientist Assitant - Computational Biology and Protein Modeling

Job Posting Title: Research Engineering/ Scientist Assitant - Computational Biology and Protein Modeling ---- Hiring Department: Oden Institute ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 20 ---- FLSA Status: To Be Determined at Offer ---- Earliest Start Date: Ongoing ---- Position Duration: Limited Duration Based on Business Need ---- 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 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. 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. 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. Purpose We are inviting highly motivated individual to join our research group at the Oden Institute, University of Texas at Austin. This 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. Responsibilities The selected candidate will work on the biological application, evaluation, and interpretation of our computational models. Depending on experience and project needs, responsibilities may include: Research 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, UniProt, Pfam, InterPro, 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 Research documentation and communication Preparing figures, structural visualizations, reports, and presentations Research coordination and collaboration 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 Required Qualifications 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. Preferred Qualifications Prior experience with protein docking, molecular dynamics, structural alignment, virtual screening, high-performance computing, or machine-learning-based structure-prediction tools is helpful but not required. Training will be provided, but candidates should be motivated to learn new computational methods and work independently. Salary Range $3,000 monthly (50% Full Time Equivalent) Working Conditions May work around standard office conditions Repetitive use of a keyboard at a workstation Use of manual dexterity Required Materials Resume/CV 3 work references with their contact information; at least one reference should be from a supervisor A brief description of your research interests and relevant experience, and any examples of previous computational or structural biology work. 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 consideration for this position. Equal Opportunity Employer: The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions. Pay Transparency: The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor\'s legal duty to furnish information. Employment Eligibility Verification: If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university. ---- E-Verify: The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university\'s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following: E-Verify Poster (English and Spanish) [PDF] Right to Work Poster (English) [PDF] Right to Work Poster (Spanish) [PDF] ---- Compliance: Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031. The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701. The University of Texas at Austin