2026 PhD Residency, Power Systems Computational Specialist for Grid Optimization (Tapestry)
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
We are seeking a PhD intern with a strong background in power systems and computational optimization to support the development of advanced grid optimization algorithms. This role focuses on improving the speed, scalability, and reliability of large-scale power system optimization problems that are critical to modern electric grid operations.
You will work closely with engineers and researchers to design, implement, and evaluate computational approaches that enable faster and more efficient grid decision-making.
How You Will Make 10X Impact
As a PhD resident, you will:
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.
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
We are seeking a PhD intern with a strong background in power systems and computational optimization to support the development of advanced grid optimization algorithms. This role focuses on improving the speed, scalability, and reliability of large-scale power system optimization problems that are critical to modern electric grid operations.
You will work closely with engineers and researchers to design, implement, and evaluate computational approaches that enable faster and more efficient grid decision-making.
How You Will Make 10X Impact
As a PhD resident, you will:
- Improve the computational performance of large-scale power system optimization algorithms used for grid planning and operations
- Develop scalable approaches that enable faster solution times for complex optimization problems
- Apply modern computing techniques to increase the size and complexity of problems that can be solved efficiently
- Collaborate with domain experts to translate theoretical methods into practical, production-ready solutions
- Optimize numerical algorithms for power system optimization problems
- Explore parallel and high-performance computing techniques to improve solver scalability
- Analyze performance tradeoffs and benchmark algorithm improvements
- Produce clear technical documentation and share findings with the broader team
- Currently enrolled in a PhD program in Electrical Engineering, Computer Science, Applied Mathematics, Physics, or a related field
- Strong foundation in power systems optimization or numerical optimization
- Experience with one or more programming languages such as Python, C++, or Java
- Familiarity with optimization methods used in power systems (e.g., optimal power flow or economic dispatch)
- Experience with high-performance or parallel computing
- Exposure to large-scale numerical solvers or scientific computing libraries
- Interest in applying research concepts to real-world engineering problems
- 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.
- 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.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.