2026/2027 PhD Residency - AI for Science, Early Stage Project

Moonshot Factory; Mountain View (CA); On-site; USD 109,000 - 157,000; Part time

Job summary

X is seeking a PhD Residency in AI for Science for Mountain View, CA. You will be embedded in a moonshot project to solve challenging research problems with autonomous AI systems.

The residency targets students actively pursuing a PhD, with hands-on work in LLM evaluation, Python, and large-scale data processing. Start dates are flexible, with opportunities to collaborate across teams and initiatives.

Qualifications

• Active enrollment in an academic program pursuing a PhD.
• Experience building autonomous AI systems or agentic workflows.
• Hands-on expertise in LLM evaluation, prompting, and large-scale data processing.
• Strong Python skills and experience with large, heterogeneous datasets, APIs, databases, and data pipelines.
• Familiarity with time-series, sequential, or panel data modelling and related methods.
• Understanding of statistical learning, out-of-sample evaluation, and back-testing.
• Experience with data integration, entity resolution, and data provenance.

Responsibilities

• Architect multi-agent systems to automate complex research and accelerate discovery.
• Fine-tune LLMs to parse unstructured data and uncover latent technological trends.

Skills

Autonomous AI

LLM evaluation

Python

Data pipelines

Time-series modelling

Bayesian modelling

Data integration

Education

PhD in quantitative/computational field

Tools

APIs

Databases

Job description

2 0 2 6 / 2 0 2 7 P h D R e s i d e n c y - A I f o r S c i e n c e , E a r l y S t a g e P r o j e c t

Internship Mountain View, CA

THE FOUNDATION OF AN AMAZING JOURNEY

Our goal at X is to make the world a radically better place. In order to do that we seek fresh unexpected perspectives, from different fields, and that's why we're excited about you.

Life here isn't easy, but it's fun. We're trying to build things most people can't even imagine, and we're doing it with the hope of making a huge, positive impact on the world. You'll be embedded into a moonshot project, where you'll partner with team members to solve key challenges.

This isn't your ordinary internship. You'll be positively challenged and pushed professionally, in ways that you may have never experienced. If this excites you - keep reading.

During your internship, you can expect:

• To be placed on one of our confidential or public X projects
• To get paid competitively and with Google benefits
• To be part of a lively community of other Interns and Residents
• To attend colloquia and discussions with team leads from across Google, DeepMind and external organizations

Requirements:

• Must be actively enrolled in an academic program and working towards completing a PhD

How you will make 10x impact:

• Architect multi-agent systems to automate complex research and accelerate discovery.
• Fine-tune LLMs to parse unstructured data and uncover latent technological trends.

Details:

• Location: X's headquarters in Mountain View, CA
• Start Date(s): Target start date of January 2, 2027 (open to rolling/flexible start dates based on project needs, university sign-off, and visa timelines).
• Duration: a flexible 4-months to 1 year program based on project team needs and your availability

What you should have:

• Experience building and deploying autonomous AI systems or agentic workflows.
• Hands-on expertise in LLM evaluation and adaptation, advanced prompting, and large-scale data processing.
• Strong Python skills and experience working with large, heterogeneous datasets, APIs, databases, and data pipelines.
• Familiarity with time-series, sequential, or panel data modelling, including some combination of state-space models, Markov-switching models, survival/hazard models, change-point detection, or event prediction.
• Understanding of statistical learning and rigorous out-of-sample evaluation, including test/train splits over time, data leakage, calibration, and back-testing.
• Experience with data integration, entity resolution, and data provenance across heterogeneous sources.

It’d be great if you also had these:

• Passion for deep-tech, R&D lifecycles, and tech commercialization.
• Background in cross-disciplinary sciences, economics, or complex systems modelling.
• Familiarity with network science, graph analytics, or knowledge graphs: citation networks, researcher networks, community detection, centrality, link prediction, graph embeddings.
• Exposure to causal inference/econometrics, including Granger causality, event studies, treatment effect thinking, and the distinction between prediction and causation.
• Knowledge of Bayesian modelling and uncertainty quantification.
• Interest or experience in scientific-paper evaluation, reproducibility, benchmarking, or automated verification of mathematical, empirical, or computational claims.
• Work experience outside of academia is plus.
• Preferred Qualifications: Ph.D. in a quantitative or computational field (e.g., Machine Learning / Artificial Intelligence / Sequence Modeling, Econometrics, Economics / Finance, Statistics / Data Science, Applied Mathematics / Computational Science, or Network Science / Complex Systems / Information Science).
• We also strongly encourage applicants with relevant research experience in related or interdisciplinary fields to apply.

The US base salary range for this position is $109,000 - $157,000 + 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.