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

Summary

X, The Moonshot Factory is focused on accelerating the transition from scientific breakthroughs to viable global solutions. They are seeking a Resident to lead the development of techno-economic models and collaborate on automating analysis workflows within their Rapid Evaluation team.

Responsibilities

• Lead the development of rigorous techno-economic models for complex physical sciences and engineering systems
• Prototype how machine learning and agentic frameworks can automate TEA workflows
• Systematically gather process models and numerical data from scientific and industry literature
• Architect rigorous systems that define system boundaries, pathways, and mass-energy balances, including yield and throughput calculations
• Perform deep-dive assessments of CAPEX and OPEX constraints, flowsheet options, and plant configurations based on market data
• Implement Monte-Carlo simulations and scenario analyses to stress-test financial models and define outcome probability distributions

Skills

• 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
• We are looking for candidates who possess 'moonshot thinking' and a desire to push the boundaries of traditional scientific modeling
• 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

Qualifications

Must Haves

• 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
• We are looking for candidates who possess 'moonshot thinking' and a desire to push the boundaries of traditional scientific modeling

Nice to Haves

• 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

Benefits

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