2026 PhD Residency, Machine Learning for the Electric Grid (Tapestry)

Google • Mountain View, CA • 2h ago

20 26 Ph DR es id en cy ,M ac hi ne Le ar ni ng fo rt he El ec tr ic Gr id (T ap es tr y)

Internship

Mountain View, CA (HQ)

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 (https://www.tapestryenergy.com/en)

About the role

As a PhD Resident in Machine Learning for the Electric Grid, you will join Tapestry's six-month PhD Residency Program to work on applied machine learning research focused on improving the quality and reliability of large-scale energy data pipelines. This role centers on developing and evaluating advanced models for cleaning, validating, and interpreting noisy data from industrial and power system networks, in close collaboration with machine learning researchers and power systems engineers.

How you will make 10X Impact

Design and evaluate Graph Neural Network (GNN)-based approaches for state estimation and data validation in power systems.

Explore methods for cleaning, validating, and modeling noisy SCADA and industrial time-series data.

Adapt and extend academic research into practical proto@types, benchmarking models against power system simulation tools (e.g., pandapower, MATPOWER).

Analyze model performance under real-world data challenges such as missing measurements, sensor failures, and outliers.

Collaborate closely with machine learning researchers and domain experts to iterate on approaches and share findings.

Clearly document results and communicate insights to inform future research and product development.

What you should have:

Currently enrolled in a PhD program (or a Master's program with equivalent research experience) in Computer Science, Electrical Engineering, Machine Learning, or a related quantitative field.

Demonstrated research experience in applied machine learning or deep learning.

Hands-on experience with Graph Neural Networks (GNNs) and modern deep learning frameworks (e.g., PyTorch, JAX).

Strong programming skills in Python and familiarity with common data science libraries.

Strong written and verbal communication skills, with the ability to explain complex technical concepts clearly.

A strong interest in decarbonizing the electric grid and building a more sustainable energy future.

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

Familiarity with streaming or real-time machine learning systems.

Experience with power system modeling, state estimation, power flow, or simulation tools such as pandapower or MATPOWER.

A track record of translating research ideas into working machine learning proto@types.

Publications in top-tier machine learning or energy-focused conferences (e.g., NeurIPS, ICML).

Experience working in a startup or high-growth research and development environment.

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.

An Equal Opportunity Workplace

At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

If you have a disability or special need that requires accommodation, please contact us at

x-accommodation-request@x.team

Google

Go to Apply

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