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

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.

• 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.

• 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…