Phaidra · Cambridge
Otherposted 7w ago
Phaidra is building the future of industrial automation.
The world today is filled with static, monolithic infrastructure. Factories, power plants, buildings, etc. operate the same they've operated for decades — because the controls programming is hard-coded. Thousands of lines of rules and heuristics that define how the machines interact with each other. The result of all this hard-coding is that facilities are frozen in time, unable to adapt to their environment while their performance slowly degrades.
Phaidra creates AI-powered control systems for the industrial sector, enabling industrial facilities to automatically learn and improve over time. Specifically:
Our team has a track record of applying AI to some of the toughest problems. From achieving superhuman performance with DeepMind's AlphaGo, to reducing the energy required to cool Google's Data Centers by 40%, we deeply understand AI and how to apply it in production for massive impact.
Phaidra’s ability to achieve its mission is determined by our ability to work together — as defined by our core values: Agency, Velocity, Craft, and Truth. We seek individuals who embody these values, as they are instrumental in ensuring our team consistently delivers excellence and fosters an engaging and supportive culture
Phaidra is based in the USA, but we are 100% remote with no physical office. We hire employees internationally with the help of our partner, OysterHR. Our team is currently located throughout the USA, Canada, UK, Sweden, Spain, Portugal, the Netherlands, Singapore, Australia, and India.
Phaidra builds autonomous AI control systems for data centre and industrial infrastructure. We deploy reinforcement learning in production on some of the world's most complex physical systems. The hard, unsolved research problems are the same ones that matter in practice. This studentship is an opportunity to work on foundational RL research while staying grounded in real-world challenges.
Reinforcement Learning (RL) has emerged as a powerful framework for sequential decision-making. Yet a fundamental limitation remains: agents trained on historical data under fixed policies often exploit spurious correlations that break at deployment time, especially when the environment shifts or the new policy explores previously unseen regions of the state-action space.
This PhD project tackles that limitation by integrating causal reasoning into RL. Causal inference provides a formal language (causal graphs, interventional queries, counterfactuals) for distinguishing stable structural relationships from incidental correlations. The research will investigate how these tools can make RL agents more robust and generalizable, particularly in real-world industrial settings.
The project will proceed in three phases:
Theoretical Foundations: formalising policy learning from biased, small datasets through a causal lens; characterising how confounding and mediators affect offline RL.
Algorithm Development: building RL algorithms that leverage known or learned causal structure to improve out-of-distribution generalisation and provide policy guarantees.
Benchmarking & Evaluation: evaluating proposed methods on controlled simulated environments with known causal structure, benchmarked against standard and offline RL baselines.
Academic Supervisor: Prof. Alessandro Abate, Department of Engineering, University of Cambridge
Industrial Co-supervisors: Dr. Miguel Suau and Dr. Alec Edwards, Phaidra
The student will be based primarily at the University of Cambridge, with the opportunity to spend time at Phaidra.
This is a fully funded 4-year PhD studentship, expected to start January 2027, co-funded by Phaidra and administered by the University of Cambridge.
You are a curious and technically rigorous researcher who wants to work at the intersection of causal inference and sequential decision-making. You are excited by foundational questions with real-world stakes and want your PhD to contribute both to the academic literature and to the practical deployment of intelligent systems.
There are two parallel steps, both required:
Both applications must be submitted. We encourage you to apply as soon as possible. Applications close 30 July 2026.
The studentship is expected to start January 2027.
Please note: Not all of Phaidra’s benefits and perks listed above apply to temporary employees such as interns.
We take a thoughtful and intentional approach to remote collaboration. Inspired by pioneers like GitLab, we embrace proven best practices to foster an exceptional remote work environment. Our culture is documentation-first, and we prioritize asynchronous communication to support focus and flexibility across time zones. While we value independence, we stay closely connected through tools like Slack and video conferencing. Weekly all-hands meetings help us align and build strong relationships, and we regularly host virtual team-building activities and social events to maintain a sense of camaraderie.
Phaidra is an Equal Opportunity Employer; employment with Phaidra is governed on the basis of merit, competence, and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status. We welcome diversity and strive to maintain an inclusive environment for all employees. If you need assistance with completing the application process, please contact us at hiring@phaidra.ai.
Phaidra participates in E-Verify, an employment authorization database provided through the U.S. Department of Homeland Security (DHS) and Social Security Administration (SSA). As required by law, we will provide the SSA and, if necessary, the DHS, with information from each new employee’s Form I-9 to confirm work authorization for those residing in the United States.
Additional information about E-Verify can be found here.
#LI-Remote
To be considered for any position at Phaidra, you must submit an online application. This role will remain open until it is filled.
Phaidra only hires individuals who are legally authorized to work in the specified location(s) above. We do not provide employment sponsorship. Candidates requiring visa sponsorship, either now or in the future, are not eligible for hire.
Candidates who advance beyond the initial screening stage will be required to sign a Non-Disclosure Agreement (NDA) in order to continue through the interview process.
All employment offers are contingent upon successful completion of employment authorization verification and applicable background checks, in accordance with local laws and company policies.
WE DO NOT ACCEPT APPLICATIONS FROM RECRUITERS.