2 x Postdoctoral Research Associate Positions in Reliable AI for Engineering

Location: London, Devon House (St Katharines Dock)

Term: 2 years, fixed term, full-time

Reports to: Professor Osvaldo Simeone

Benefits: The university supports staff maintaining a good work-life balance, offering: (i) flexible working and parental leave opportunities; (ii) an employee assistance programme which provides free, confidential advice on both home and work concerns, as well as optional private medical insurance; (iii) season ticket loans; and (iv) being part of the cycle-to-work scheme.

Start: 1^st February 2026 

The Role 

Northeastern University London invites applications for two Post-Doctoral Research Associates positions in Reliable AI for Engineering to work with Professor Osvaldo Simeone.  The successful candidates will work on the development of a theoretically grounded framework for statistically reliable AI, with applications to engineering. The research will focus on the design of formal reliability guarantees for black-box AI models operating under highly non-deterministic and context-dependent conditions, such as those arising in next-generation communication networks. 

The candidate will contribute to topics including:

• The offline calibration of pre-trained AI models through hyperparameter optimization and conformal prediction methods;
• The online monitoring of model reliability and performance indicators in dynamically changing environments;
• The integration of synthetic data from digital twins using prediction-powered inference to enhance reliability assessment;
• The theoretical analysis and algorithmic development of methods rooted in statistical learning theory, multiple hypothesis testing, and online convex optimization.

This work is part of the ERC Advanced Grant project CONTRACT, which seeks to redefine the role of AI in wireless networks—from a potential reliability concern to a verifiable and dependable system component. 

Core duties include:

• Conducting independent and collaborative research in statistically reliable AI, with a focus on conformal prediction, reliable inference, and learning with synthetic or simulated data.
• Developing and analyzing new algorithms for AI calibration, run-time reliability monitoring, and adaptive decision-making in wireless environments.
• Collaborating closely with project partners across academia and industry, contributing to cross-disciplinary research spanning AI, statistics, and wireless communications.
• Publishing results in top-tier journals and conferences in machine learning, statistics, and communications.
• Presenting research findings at project meetings, workshops, and international conferences.
• Supporting the supervision of PhD students and undergraduate research assistants working within the CONTRACT project.
• Contributing to the writing of project deliverables, reports, and funding documentation. 

We particularly encourage applications from those belonging to groups underrepresented in UK higher education. 

About the Faculty 

The Institute for the Wireless Internet of Things (WIoT) at Northeastern University London focuses on advancing next-generation wireless systems and intelligent connectivity. Building on WIoT’s global research leadership, the London campus brings together expertise in AI, neuromorphic computing, and wireless communications to explore transformative technologies for 6G and beyond. The institute fosters close collaboration with industry and academia, providing an interdisciplinary environment for innovation, hardware prototyping, and impactful real-world research. 

The Faculty of Computing, Mathematics, Engineering, and Natural Sciences (CoMENS) is undergoing significant growth at Northeastern University London. It is home to four interdisciplinary undergraduate dual-degree (in UK and US) programmes in the areas of Data Science, Data Science and Politics, Computer Science and Business, and Computer Science and Philosophy; four postgraduate programs in the areas of AI Ethics, Data Science, Computer Science, and Technology Leadership; and five degree apprenticeship programmes in the areas of AI, Data Science, Digital and Technology Solutions, and Biosciences. 

The faculty plays a major part in Northeastern University’s first-year student mobility program, offering undergraduate courses in Computer and Data Science, Mathematics, Engineering, Physics, Biology, Chemistry and Healthcare, striving to inspire and equip entering students to be outstanding scientists. 

About the University 

Founded in 2012, Northeastern University London (formerly known as New College of the Humanities) has established itself as a prestigious higher education institution based in the heart of London. Northeastern University London is part of Northeastern University’s Global Campus Network. Positioned as top ranking in the USA, Northeastern has campuses in Arlington, Boston, Charlotte, Miami, Oakland, San Jose, and Seattle in the USA, and Toronto and Vancouver in Canada.

After becoming part of Northeastern University’s global network in early 2019, the University has undergone a period of rapid growth, having been granted Taught Degree Awarding Powers in February 2020 and moved to a new, state-of-the-art campus in 2021.  

Northeastern University London offers a vibrant, collegiate community delivering broad and academically rigorous degree programmes, designed to equip graduates with the combination of skills and knowledge that are increasingly desired by organisations, employers, and society. It offers state of the art audio visual technology in its teaching and meeting spaces across the organisation. 

Person Specification Criteria 

To undertake this role, the following should apply – should you not have the experience below, please do highlight where transferable skills would assist with you undertaking the role. 

Qualifications 

• PhD, or equivalent professional experience, in Machine Learning, Statistics, Electrical Engineering, Computer Science, or a related field. 

Key Criteria 

• Demonstrated experience with mathematical modelling, algorithm design, or theoretical analysis of learning systems.
• Proficiency in Python
• Background in statistical learning theory, conformal prediction, multiple hypothesis testing, or reliable inference
• Demonstrated ability to plan, execute, and publish research
• Excellent written and verbal interpersonal communication skills
• Excellent time-management and organisational skills 

Additional Information 

Enquiries 

Informal enquiries may be made to Professor Osvaldo Simeone (o.simeone@nulondon.ac.uk). However, all applications must be made in accordance with the application process specified. 

Application Process 

Applications should be made via the 'Apply' button above by 23:59 on 27 February 2026. 

Applications must include a CV and covering letter of no more than one page that addresses the criteria for the role and includes names and contact information of up to three references. References will only be sought for short-listed candidates. 

Interviews are expected to take place between 9/3/2025 and 13/3/2025. 

The panel will be shortlisting for this position on a rolling basis so please apply as soon as possible. We reserve the right to close this post before the closing date if we receive a large number of applications. 

Please note this role may require a basic or enhanced DBS check. Our organisation acknowledges the duty of care to safeguard, protect and promote the welfare of our students and staff, and is committed to ensuring safeguarding practice reflects statutory responsibilities, government guidance and complies with best practice and Ofsted requirements. You must adhere to the above if you are offered a role with NU London. 

Applications are welcome from all sections of the community and will be judged on merit alone. We welcome applications from underrepresented groups. Candidates must be able to demonstrate their eligibility to work in the UK in accordance with the Immigration, Asylum and Nationality Act 2006. 

Job sponsorship. Visa sponsorship will be available for a successful candidate for this position.