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

Salary$109k – $157k
LocationMountain View, CA (HQ), Mountain View, CA
Work modeon-site
Typeinternship
SeniorityEntry
DepartmentInternship
Company size501–1,000 people
First seenOct 4, 2026 · 1w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Must have7
Must be actively enrolled in a PhD program at a university
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 backtesting
Experience with data integration, entity resolution, and data provenance across heterogeneous sources
Nice to have8
Passion for deep-tech, R&D lifecycles, and tech commercialization
Background in cross-disciplinary sciences, economics, or complex systems modeling
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 a plus
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)
Eligibility1
We also strongly encourage applicants with relevant research experience in related or interdisciplinary fields to apply
Skills
Python
LLMs
NLP
APIs
databases
data_pipelines
state-space_models
Markov-switching_models
survival/hazard_models
change-point_detection
event_prediction
time-series_analysis
panel_data_modelling
network_science
graph_analytics
knowledge_graphs
causal_inference
Bayesian_modelling
uncertainty_quantification
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.
About the role
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 a PhD program at a university
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 backtesting.
•
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 modeling.
•
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.
Additional public information:
•
https://www.wired.com/video/watch/astro-teller-captain-of-moonshots-at-x-speaks-at-wired25
•
https://www.bloomberg.com/news/videos/2019-10-10/alphabet-x-s-astro-teller-on-bloomberg-studio-1-0-video
•
https://www.npr.org/2025/09/12/nx-s1-5493348/astro-teller-takes-us-inside-the-moonshot-factory-building-tech-ahead-of-its-time
•
https://time.com/collections/best-inventions-2024/7094574/x-taara/
•
https://youtu.be/_iLJU4HORAA?si=aK8cHf64NUNcsZXr
•
https://www.fastcompany.com/best-workplaces-for-innovators/list/84
Legal
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.
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