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Opportunity Details

Cambridge Mathematical Innovation Research Associate (Fixed Term)

Salary
GBP 38,448 - 46,970 per year
Application Deadline
December 15, 2026
Position Type
Researcher
Date Posted
November 3, 2026
Contact Email
sb2116@cam.ac.uk
Source details may be limited

Some structured details on Opportunita may still be incomplete. Please read the official university page before applying.

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Offer Summary

The University of Cambridge seeks a Cambridge Mathematical Innovation Research Associate for its CHIMiRA hub. This fixed-term role, available at Research Associate or Senior Research Associate levels, focuses on enhancing the real-world impact of mathematical research through interdisciplinary projects and industrial collaborations. The position offers an annual salary between £38,448 and £46,970. Candidates must hold a PhD in Statistics, Data Science, or a related field, with demonstrated experience in statistical disciplines, machine learning, or AI. Strong communication skills are essential for engaging non-technical audiences and building industry partnerships. Responsibilities include managing research projects, writing grants, and potentially supervising students. The ideal candidate possesses entrepreneurial interest and coding proficiency. The contract is initially for two years, with a preferred start date of February 2027.

Generated from stored offer content. Always confirm details in the official posting.

Project Description

A position exists for a Cambridge Mathematical Innovation Research Associate (CaMIRA) in the Department of Pure Mathematics and Mathematical Statistics to work within the recently established Cambridge Hub for Innovative Mathematics in Research and Applications (CHIMiRA). The position will be appointed at either a Research Associate or a Senior Research Associate level, depending on experience.

The purpose of CHIMiRA is to improve the real-world impact of research generated at the University of Cambridge by undertaking highly interdisciplinary academic projects, industrial collaborations, and consultancy engagements.

The successful candidate will join a small team of CaMIRAs, who typically work on a portfolio of short-to medium term projects funded by academic or industrial partners. The role will be very flexible, in both application area and project type, and the ideal candidate would necessarily be required to have developed skills in several areas of Statistics, be eager to learn techniques from different statistical disciplines, machine learning, and AI, and have excellent communication skills to scope ideas, co-design projects, and articulate statistical concepts to a non-technical audience. Prior industrial experience would be desirable, but a positive attitude to industrial engagement is essential. The role requires strong skills in interpersonal communication, relationship building, time management, manuscript preparation, and grant writing.

CHIMiRA is a self-funded Hub and requires ongoing research and industrial funding to support its research activities. Therefore, the successful candidate will be proactive in initiating collaborations with research groups throughout the University and in Industry, engaging with the wider UK Innovation Research Associate network, and communicating CHIMiRA's activities to a wide audience. They should have experience/interest in entrepreneurial activities, such as research commercialisation, intellectual property protection and/or translational research.

Duties include developing and conducting individual and collaborative research objectives, proposals, and projects. The role holder will be expected to plan and manage their own research and administration, with guidance if required, and to assist in the preparation of proposals and applications to external bodies. You must be able to communicate material of a technical nature and be able to build internal and external contacts. You may be asked to assist in the supervision of student projects, the development of student research skills, provide instruction, or plan/deliver seminars relating to the research area.

The successful candidate will have a PhD in Statistics, Data Science, or a similar discipline, may have completed a postdoctoral position or position in industry before, and possess experience in several areas of Statistics. We expect the successful candidate to have seen one or more projects through to completion, preferably with an application of their research in a real-world setting. Coding and software engineering proficiency will be expected if relevant to their experience, e.g. for machine learning challenges. Fixed-term: The funds for this post are available for two years in the first instance, and the post may, subject to the availability of funding, be further renewed for a period or periods.

Preferred start date: February 2027, with mutual agreement

Interviews will likely take place in the first half of January.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please indicate the contact details of three academic referees, including their email addresses, on the online application form and upload a full curriculum vitae and a description of your recent research and/or projects (not to exceed three pages). Please note that we will assume that you are happy for us to approach your referees at any stage, unless you indicate otherwise in the space provided on the form.

Informal inquiries can be made by contacting Professor Sergio Bacallado de Lara at sb2116@cam.ac.uk or Professor Sofía Villar at sofia.villar@mrc-bsu.cam.ac.uk.

If you have any queries regarding the application process, please contact us via email at LF51556@maths.cam.ac.uk.

Please quote reference LF51556 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.


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Last Update University of Cambridge cam.ac.uk
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