2026 PhD / Master's Residency - Rapid Evaluation Techno-Economic Analysis (TEA)

InternshipMountain View, CA

The Moonshot

At X, we believe that the gap between a scientific breakthrough and a viable global solution shouldn't be a decades-long manual crawl. We are building the Agentic Techno-Economic Framework, an intelligent system designed to automate the evaluation of emerging technologies. By bridging engineering complexity and economic reality, we aim to accelerate the path from "what if" to "how soon".

The Project: Revolutionizing Technical Due Diligence

Techno-Economic Analysis (TEA) is traditionally a slow, iterative process requiring manual synchronization between energy balances and financial spreadsheets. You will be embedded within X’s Rapid Evaluation team, using your expertise in building out TEAs and collaborating with agentic experts to automate and accelerate TEA workflows. Your work will focus on creating a system that not only gathers data but builds trust through explicit mapping of assumptions and literature references.

How you will make 10x impact:

As a Resident, you will lead the development of rigorous techno-economic models for complex physical sciences and engineering systems. You will have the opportunity to prototype how machine learning and agentic frameworks can automate these workflows. You will contribute your TEA expertise and collaborate with teams at X on the following modules:

  • Literature Exploration: Systematically gather process models and numerical data from scientific and industry literature
  • Process Flow Development: Architect rigorous systems that define system boundaries, pathways, and mass-energy balances, including yield and throughput calculations, as the core of techno-economic models.
  • Economic Research: Perform deep-dive assessments of CAPEX and OPEX constraints, flowsheet options, and plant configurations based on market data.
  • Uncertainty Quantification: Implement Monte-Carlo simulations and scenario analyses to stress-test financial models and define outcome probability distributions.

This project aims to push the limits of science and modeling as we know them and to prove how ML can radically accelerate our understanding of the world

  • Location: X's headquarters in Mountain View, CA
  • Start Date(s): Year-round rolling basis
  • Duration: a flexible 4 mo. to 1 year program based on project team needs and your availability

Throughout your AI Residency you can expect:

  • To be embedded into one of our confidential or public X projects
  • To get paid competitively and receive benefits
  • To be a part of a lively community of AI and ML Residents
  • To attend tech-talks with AI leaders from across X

What you should have:

  • We are looking for candidates who possess "moonshot thinking" and a desire to push the boundaries of traditional scientific modeling.
  • Currently enrolled in a Masters or PhD program in engineering, science, or related field.
  • Experience building comprehensive techno-economic analysis (TEA) and scenario models, ideally having used tools like Aspen HYSYS, Aveva, ChemCAD, DWSIM, etc.
  • Proficiency in process modeling (mass/energy balances), financial modeling, and uncertainty quantification (e.g., Monte Carlo).
  • Interest and passion in building moonshot technologies.

It’d be great if you also had these:

  • Industry experience in physical or applied science fields either in job experience or through academic partnerships with industry
  • Comfort with ambiguity and a high "failure tolerance"—the ability to walk away from a project if the data suggests it isn’t promising
  • Interest or experience with using LLMs, agentic workflows, and application frameworks like Langchain, VertexAI, etc. to complement physical sciences research

Additional public information:

https://www.wired.com/video/watch/astro-teller-captain-of-moonshots-at-x-speaks-at-wired25

https://www.bloomberg.com/news/videos/2019-10-10/alphabet-x-s-astro-teller-on-bloomberg-studio-1-0-video

The US base salary range for this position is $100,000 - $147,000 + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.

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