2026 PhD Residency, Machine Learning for Grid Simulations (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
This PhD residency focuses on advancing machine-learning-driven approaches for power grid simulations, with an emphasis on improving the speed, accuracy, and numerical stability of large-scale transient simulations. You will work closely with power systems and simulation experts to apply modern ML techniques to real-world grid modeling challenges.
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
This PhD residency focuses on advancing machine-learning-driven approaches for power grid simulations, with an emphasis on improving the speed, accuracy, and numerical stability of large-scale transient simulations. You will work closely with power systems and simulation experts to apply modern ML techniques to real-world grid modeling challenges.
How You Will Make 10X Impact
As a PhD resident, you will:
- Accelerate grid simulations by developing machine learning models that reduce computational cost while preserving physical accuracy.
- Advance state-of-the-art ML methods for modeling complex grid components, building on and improving existing simulation baselines.
- Partner with power system experts to integrate ML techniques directly into simulation workflows used for planning, reliability analysis, and outage prevention.
- Improve numerical stability and performance of transient simulations by applying physics-informed and data-driven modeling approaches.
- Deliver production-ready research outputs that strengthen core simulation technology and influence future product direction.
- Currently enrolled in a PhD program (or exceptional MS) in a STEM field such as Computer Science, Electrical Engineering, Computer Engineering, Physics, Mathematics, or a related discipline.
- Strong foundation in machine learning concepts and methods.
- Experience with one or more general-purpose programming languages (e.g., Python, C/C++, Java).
- Interest in or exposure to power systems, power electronics, or numerical simulations.
- Ability to work independently on research-driven problems and collaborate across disciplines.
- Experience with physics-informed machine learning or scientific ML.
- Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX).
- Background in scientific computing or numerical methods.
- Prior work on simulation-heavy or computationally intensive systems.
- 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.