Postdoctoral Fellow in Energy and Resource Systems

Job Posting Title: Postdoctoral Fellow in Energy and Resource Systems Hiring Department: Bureau of Economic Geology Position Open To: All Applicants Weekly Scheduled Hours: 40 FLSA Status: Exempt from FLSA Earliest Start Date: Immediately Position Duration: Expected to Continue Until Aug 10, 2027 Location: PICKLE RESEARCH CAMPUS Job Details General Notes This position is located at the J.J. Pickle Research Campus in North Austin. The Center for Energy Economics at the Bureau of Economic Geology is recruiting a postdoctoral researcher for COMPASS (Collaborative Optimization & Management of Power Allocation, Surface & Subsurface strategies), our Industrial Affiliates research consortium on large-load industrial growth in Texas — data centers, oil and gas operations, advanced manufacturing, refining, and mining — and the pressure that growth places on shared energy, water, land, and community systems. Purpose Build and apply quantitative and economic models to assess the resource, infrastructure, and energy requirements of large-load industrial development in Texas. Design and maintain the databases and quantitative models supporting economic valuation of infrastructure and resource options, including cross-sector co-location. Conduct geospatial and data science analysis supporting site suitability, resource constraint mapping, scenario planning, and the COMPASS interactive visualization and mapping database. Translate results into consortium deliverables, peer-reviewed publications, and stakeholder-facing briefings that help translate research into real-world decisions. Responsibilities Assess the resource, infrastructure, and demand requirements of large-load industrial development, including energy, water, and land use, and competing claims on shared resources. Conduct integrated geospatial analyses for optimal siting, balancing access to water, land, generation resources, transmission, and existing industrial infrastructure, and evaluate synergies from co-locating complementary industries. Build and apply quantitative and economic models to quantify cost, reliability, and trade-offs across development scenarios, and develop projections of industrial resource and energy demand at high spatial and temporal resolution. Build a system modeling framework to evaluate the deliverability of large-load projects, including interconnection, capacity, and infrastructure constraints. Design, build, and maintain the databases and data pipelines that power COMPASS research, integrating large multi-source datasets (including ERCOT and EIA records) into reproducible analytical systems. Conduct independent research, and develop grant proposals. Present research to COMPASS Industrial Affiliates members, community stakeholders, and policymakers at consortium meetings, workshops, and short courses; contribute to member-facing forecasting reports, white papers, and policy briefs. Publish in BEG Reports of Investigation; peer reviewed, international, journals; and informal outlets. Develop and maintain the analytical, database, and computing infrastructure that forms the basis for these studies, including high performance computing workflows, geospatial data pipelines, and the interactive visualization and mapping database delivered to consortium members. Mentor graduate and undergraduate student researchers. Required Qualifications PhD in resource or environmental economics, economics, energy systems engineering, industrial engineering, operations research, data science, water or environmental resources engineering, geosciences, or a closely related quantitative field. Degree must have been earned within 3 years from date of hire. Demonstrated record of research communication, including peer-reviewed publication, and the ability to communicate quantitative results to non-technical audiences. Excellent teamwork, communication, and organizational skills; a self-starter who learns new subject areas quickly and stays focused on execution. Genuine curiosity about fast-growing, fast-changing sectors and comfort working in a fast-paced, collaborative team. Demonstrated research experience in quantitative modeling and database or data systems engineering. Prior research experience with large, heterogeneous databases and quantitative models. Documented capabilities in programming like Python, R, SQL, or Julia. Proficient in Excel and PowerPoint. Preferred Qualifications Geospatial modeling and analysis is a preferred skill, including GIS, spatial suitability modeling, multi-criteria decision methods, and machine-learning-based feature importance. Exposure to resource questions relevant to large-load development, such as water, land, or energy, is welcome; this subject matter can be developed on the job. Regional economic or fiscal impact analysis. Familiarity with data center, industrial load, or large-load infrastructure development. Familiarity with electricity markets and power system modeling, including ERCOT market structure and data, is desirable but not required. Experience applying machine learning or AI and large language model methods to extract structured information from regulatory, permitting, water rights, or filing documents. Experience producing stakeholder-facing deliverables for industry, agency, or community audiences. Experience mentoring students. Salary Range $65,000 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 Occasional interstate, intrastate and international travel Required Materials Resume/CV 3 work references with their contact information Letter of interest Employment Eligibility Please make sure you meet all the required qualifications and you can perform all of the essential functions with or without a reasonable accommodation. 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. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 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. 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