2026 PhD Residency, Software Engineering-Socio-Environmental Risk Modeling (Tapestry)

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About Tapestry

Tapestry is Alphabet’s moonshot for the electric grid, working at the frontier where energy’s complexity meets AI’s potential. We were born at X, the innovation lab responsible for breakthrough technologies like Waymo, Verily and Google Brain.

To keep pace with humanity’s growing energy needs, the world needs a grid that is visible and understandable. We provide that clarity by building advanced, AI-enabled analytical and planning tools that allow the entire energy ecosystem to plan smarter, move faster, and operate more efficiently—ensuring electricity remains reliable and affordable for everyone.

This is a global effort. Tapestry is proud to support partners in the U.S., U.K., Chile, New Zealand, Australia and Brazil as they build a cleaner, more resilient energy future. Joining Tapestry allows you to do the best work of your life as part of a multidisciplinary team of experts in AI, energy systems, software engineering and product design—all collaborating to reshape energy on a global scale. If you want to tackle problems that matter and build tools with real impact, we would love to meet you. Learn more about our team and our mission here.

About The Role

This 6-month PhD program focuses on building software systems that integrate economic, environmental, regulatory, and public-perception data to model non-technical risks in large infrastructure projects. You will design and implement data pipelines, analytical models, and prototypes that transform diverse data sources into actionable risk insights.

This is a hands-on role with strong analytical depth. We are looking for someone who is interested in the intersection of data-heavy applications, high-performance engineering, and the responsible, intentional application of technology to navigate societal complexity and global problems.

How You Will Make 10X Impact

  • Bridge technical and human context: Navigate the nuance between hard data and social impact, ensuring that software models remain grounded in real-world consequences and ethical data stewardship.
  • Enable earlier decision-making: Build software pipelines that surface non-technical risks earlier in the project lifecycle, reducing costly downstream surprises.
  • Unify fragmented data: Integrate structured and unstructured data sources into a cohesive, analyzable system.
  • Improve modeling speed: Develop efficient workflows that accelerate experimentation and iteration across economic and policy-related signals.
  • Increase interpretability: Translate complex analytical outputs into clear, explainable insights through well-designed interfaces or prototypes.
  • Support real-world outcomes: Help inform decisions that balance cost, environmental considerations, and public acceptance.

What You Should Have

  • PhD student in Computer Science, Software Engineering, Data Science, Economics, or a related field
  • Strong proficiency in Python, Java, or Kotlin for data processing and modeling
  • Experience building data pipelines, APIs, or analytical workflows
  • Familiarity working with large, messy, or unstructured datasets
  • Ability to design maintainable, well-structured software systems
  • Strong analytical thinking and problem-solving skills

It’d be great if you also had one or more of these:

  • Experience with natural language processing or text analysis
  • Exposure to geospatial or spatially indexed data
  • Familiarity with statistical or econometric modeling concepts
  • Experience building dashboards or lightweight data visualizations
  • Interest in applied research that bridges analysis, software systems, and responsible application of technology to complex socio-environmental ecosystems and large-scale corporate frameworks

Our values

  • Take charge: We take initiative and own outcomes that move the mission forward.
  • Transform with purpose: We build solutions that solve real problems and create meaningful impact.
  • Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
  • Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
  • Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What We Offer

  • Competitive salary
  • Medical, dental, and vision coverage
  • A culture that supports growth, ownership, and meaningful impact, along with:
  • Immersion in a world-class research environment at the intersection of AI and climate tech.
  • Competitive residency stipend and housing relocation support for the duration of the program.
  • Direct mentorship from industry-leading research scientists and engineers.
  • Opportunity to work on "moonshot" problems with access to Alphabet-scale compute and resources.

The US base salary range for this position is $109,000 - $150,000 + 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.