At a Glance
- Tasks: Join a cutting-edge research team developing reliable AI frameworks across neuromorphic, classical, and quantum systems.
- Company: Northeastern University London, a prestigious institution in the heart of London.
- Benefits: Flexible working, 25 days annual leave, health support, and professional development opportunities.
- Other info: Dynamic growth environment with opportunities for mentorship and collaboration.
- Why this job: Make a real impact in AI research while collaborating with top experts in an innovative environment.
- Qualifications: PhD in relevant fields and experience in algorithm design or statistical analysis.
The predicted salary is between 42701 - 42701 £ per year.
About the Opportunity
Position Overview
- Discipline: Engineering
- Faculty: Computing, Mathematics, Engineering and Natural Sciences (CoMENS)
- Location: London, Devon House (St Katherines Dock)
- Term: 2 years, fixed term, full-time
- Salary Range: £42,701 per role (may be appointed at a higher spine point if more experienced).
- Reports to: Professor Osvaldo Simeone
Benefits
The university supports staff maintaining a good work-life balance, offering:
- Flexible working and parental leave opportunities
- An employee assistance programme which provides free, confidential advice on both home and work concerns, as well as optional private medical insurance
- Season ticket loans
- Being part of the cycle-to-work scheme
Start: October 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.
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 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 the 1st of June and the 5th of June 2026. 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 may be available for a successful candidate for this position.
About the University: Northeastern University London (NU London) is a prestigious higher education institution based in the heart of London and is part of Northeastern University’s global campus network. Overlooking the River Thames near Tower Bridge, NU London offers academically challenging educational programmes designed to inspire innovative thinking, encourage interdisciplinary study, and provide global experiences. The bright and modern campus offers award winning, contemporary facilities for students and staff including state of the art audio visual technology in its teaching and meeting spaces. Inspired by excellence, infused with an energy of ideas and ability in motion, at NU London, being a part of our staff is to be a part of a collective of entrepreneurs and educators, builders and thinkers. NU London is growing quickly, offering opportunity and growth for our staff. Currently hosting 1,500 students, our aim is to have 4000 students by 2028/29.
Choose NU London: As well as the exciting opportunities this role presents, the University supports staff maintaining a good work/life balance, your health and wellness are of utmost importance to us, and our offerings encompass:
- 25 days annual leave, plus 8 bank holidays and winter break holidays (normally 2 days between Christmas and New Year)
- Access to personalised Continuous Professional Development (CPD) plans and opportunities
- Support with private medical insurance
- Eye test reimbursement
- Cycle Scheme vouchers
- 24/7 employee assistance/ support via our Employee Assistance Programme
- Access to deals and discounts for food & shopping in the local area
For staff’s own wellbeing, for part time roles, the expectation is if you have multiple roles, they should not exceed full time (37.5 hours per week), and for full time roles, the expectation is that this will be your only role (apart from intermittent roles).
Postdoctoral Research Associate in Reliable Neuromorphic, Classical, and Quantum AI in London employer: Northeastern University
Northeastern University London is an exceptional employer, offering a vibrant work culture that prioritises work/life balance and employee wellbeing. With a commitment to professional development, flexible working arrangements, and a supportive environment for innovative teaching, staff are empowered to grow and thrive in their careers while contributing to a dynamic educational community in the heart of London.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Research Associate in Reliable Neuromorphic, Classical, and Quantum AI in London
✨Tip Number 1
Network like a pro! Reach out to your connections in academia and industry, especially those who might know Professor Osvaldo Simeone or are involved in AI research. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Prepare for the interview by diving deep into the latest trends in reliable AI, neuromorphic computing, and quantum machine learning. Show us you’re not just knowledgeable but passionate about these fields—this will definitely make you stand out!
✨Tip Number 3
Don’t forget to showcase your collaborative spirit! Highlight any past experiences where you’ve worked with diverse teams or contributed to cross-disciplinary projects. We love candidates who can bring people together to tackle complex challenges.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we’re always on the lookout for talent that aligns with our mission at Northeastern University London.
We think you need these skills to ace Postdoctoral Research Associate in Reliable Neuromorphic, Classical, and Quantum AI in London
Some tips for your application 🫡
Tailor Your Cover Letter:Make sure your cover letter speaks directly to the role. Highlight your experience in AI, machine learning, or any relevant projects that align with the job description. We want to see how you fit into our vision!
Showcase Your Research Skills:In your CV, emphasise your research experience and any publications you've contributed to. Mention specific algorithms or methodologies you've worked with, especially those related to reliability and calibration in AI.
Keep It Concise:Remember, your covering letter should be no more than one page. Be clear and concise about your qualifications and why you're excited about this opportunity. We appreciate brevity and clarity!
Apply Early!:Since we’re shortlisting on a rolling basis, don’t wait until the deadline! Get your application in as soon as possible through our website. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Northeastern University
✨Know Your Stuff
Make sure you brush up on the latest trends in reliable AI, especially in neuromorphic and quantum computing. Familiarise yourself with key concepts like uncertainty quantification and calibration methods. This will not only help you answer technical questions but also show your genuine interest in the field.
✨Showcase Your Research Experience
Prepare to discuss your previous research projects in detail. Highlight any relevant experience with algorithm design or statistical learning theory. Be ready to explain how your work aligns with the role's focus on developing reliable frameworks for AI systems.
✨Ask Thoughtful Questions
Interviews are a two-way street! Prepare insightful questions about the research programme, collaboration opportunities, and the team dynamics. This shows that you're not just interested in the position, but also in how you can contribute to the university's goals.
✨Practice Your Presentation Skills
Since you'll be expected to present findings at meetings and conferences, practice explaining your research clearly and concisely. Use visuals if possible, and be prepared to engage in discussions about your work. This will demonstrate your communication skills and ability to collaborate effectively.