Job Description

Discipline: Engineering
Location: London, Devon House (St Katherines Dock)
Term: 2 years, fixed term, full-time
Direct Reports: None
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: any time after March 2026
The Role
Northeastern University London invites applications for three Post-Doctoral Research Associates in Reliable Neuromorphic, Classical, and Quantum AI to work with Professor Osvaldo Simeone. The successful candidates will join an ambitious research programme aimed at developing theoretically principled and statistically reliable frameworks for next-generation AI, spanning classical, neuromorphic, and quantum paradigms with application to engineering.
The research will focus on the foundations of reliability, uncertainty quantification, and calibration in AI models, addressing the challenges posed by non-deterministic, data-limited, and dynamically evolving environments. Applications include complex engineered systems such as intelligent communication networks, distributed computing platforms, and quantum-enhanced processors.
The candidates will contribute to topics including:

• The offline and online calibration of learning systems through methods such as conformal prediction, hyperparameter optimization, and reliable inference in engineered systems, including telecom networks;
• The development of neuromorphic algorithms and spiking neural models with built-in efficiency and reliability guarantees;
• The design of reliability frameworks for quantum machine learning, including conformal quantum prediction and uncertainty quantification in quantum models;
• Theoretical and algorithmic advances rooted in statistical learning theory, online convex optimization, and multiple hypothesis testing;
• The use of synthetic and quantum-generated data to support model assessment and adaptive decision-making.

Core duties include:

• Conducting independent and collaborative research in reliable and statistically grounded AI, for classical, neuromorphic, and/or quantum systems.
• Developing and analyzing new algorithms for calibration, reliability monitoring, and adaptive decision-making.
• Collaborating closely with international partners in academia and industry, contributing to cross-disciplinary research at the interface of AI, information theory, and physics.
• Publishing results in leading journals and conferences in machine learning, information theory, and quantum information.
• Presenting research findings at project meetings, workshops, and international symposia.
• Supporting the supervision and mentoring of PhD students and research assistants within the group.
• Contributing to the preparation of project deliverables, reports, and future funding proposals.

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, quantum machine learning, neuromorphic computing, 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 07 January 2026. Participation in the equal opportunities section is encouraged, but voluntary.
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.
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 sufficient number of qualified 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 may be available for a successful candidate for this position.
42,701. Grade 6, pt 32 per role, per annum (may be appointed at a higher spine point if more experienced)

Skills Required