Postdoctoral Research Associate/Fellow (Technical AI Safety)

King's College London; City Of London; On-site; GBP 40,000 - 50,000; Full time

Job summary

A leading educational institution in London is seeking a Postdoctoral Research Associate to focus on technical AI safety. This role involves developing methods for probing large language models and working in a vibrant research environment alongside top researchers. Candidates should have or be close to completing a PhD and demonstrate strong research skills and creativity. This is a full-time position with a fixed-term contract until October 2027.

Benefits

At least 10 days per year for professional development

Qualifications

• Completed or near completion of a PhD in a relevant discipline.
• Outstanding research track record in topics related to AI safety.
• Demonstrated scientific creativity and research independence.

Responsibilities

• Develop methods for latent probing of large language models.
• Work with a core team on AI safety research.
• Support junior team members and engage in dissemination activities.

Skills

Algorithmic and model development skills

Research experience in relevant techniques

Strong publication record

Effective communication (written and verbal)

Ability to work independently

Education

PhD in relevant subject area

Tools

Familiarity with relevant machine learning libraries

Job description

About us

The Department of Informatics at King's College London is looking to appoint a Postdoctoral Research Associate or Fellow to work in the area of technical AI safety.

About the role

The position is funded by the Open Philanthropy grant "Verifiably Robust Conformal Probes". The project's goal is to develop methods for latent probing (aka activation monitoring) of large language models (LLMs) that leverage certification and conformal prediction techniques to offer probabilistic and adversarial robustness guarantees. Applications include detection of misaligned LLM intentions such as deception, harmfulness, jailbreaking, and power-seeking behaviours.

You will work alongside Dr Nicola Paoletti and a core team that includes a PhD student from Dr Paoletti's lab, Prof Osvaldo Simeone from the Department of Engineering at King's College London, and Dr Mehran Hosseini from the University of Manchester. You will join a vibrant research environment, with several researchers in Dr Paoletti's lab working on related topics, within a department that has a strong track record in AI research.

Applicants for the associate position should have already completed, or be close to completing, a PhD in a relevant discipline. Applicants for the fellow position should also have prior post-doc experience. Commensurate with their career stage, applicants should have an outstanding research track record in topics related to the project's scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference.

Applicants should demonstrate scientific creativity, research independence, the capacity to support junior team members, and strong communication skills, both written and verbal.

This is a full time post (35 hours per week), and you will be offered a fixed term contract until 31 October 2027 and starting as soon as possible.

Research staff at King's are entitled to at least 10 days per year (pro-rata) for professional development.

About you

To be successful in this role, we are looking for candidates to have the following skills and experience:

• Essential criteria (Grade 6, Research Associate)
• PhD in relevant subject area (or near completion of)
• Research experience in relevant research techniques and methodologies
• Strong publication record commensurate with the applicant's career stage
• Algorithmic and model development skills, and a familiarity with relevant machine learning libraries
• Ability to work independently and within a team
• Effective communication: written and verbal

• Desirable criteria (Grade 6, Research Associate)
• Creativity and originality in research
• Willingness to engage in dissemination activities beyond conference presentations (e.g., present in lab meetings or research visits)

• Essential criteria (Grade 7, Research Fellow)
• PhD in relevant subject area
• Prior post-doc experience
• Research experience in relevant research techniques and methodologies
• Strong publication record commensurate with the applicant's career stage
• Algorithmic and model development skills, and a familiarity with relevant machine learning libraries
• Ability to work independently and within a team
• Effective communication: written and verbal

• Desirable criteria (Grade 7, Research Fellow)
• Experience supporting junior colleagues (e.g., MSc and PhD students)
• Creativity and originality in research
• Willingness to engage in dissemination activities beyond conference presentations (e.g., present in lab meetings or research visits)

Downloading a copy of our Job Description

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process.

* Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.

Further Information

We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community.

We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's.

As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities.

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

To find out how our managers will review your application, please take a look at our How we Recruit pages.

Interviews are due to be held in late November 2025.