Research Associate in Rough Path Theory for Applications

Location: South Kensington Campus

About the role:

Applications are invited for a Postdoctoral Research Associate to Join a world-leading team of mathematical scientists at Imperial College London working on the EPSRC Programme Grant DataSig II, a transformative initiative at the intersection of rough path theory and modern machine learning. This ambitious, multi-institutional collaboration aims to redefine how streamed data is modelled and processed—unlocking new capabilities in generative AI, anomaly detection, and real-time decision-making.

What you would be doing:

Key scientific challenges you’ll help tackle:

• Next-generation Transformers: Develop mathematically grounded architectures for continuous, multimodal data streams.
• Efficient Representations: Create robust, interpretable, and scalable representations using signature and path development techniques
• Anomaly Detection: Build principled, representation-invariant methods for identifying outliers in high-dimensional data with use in appllications.

The postholders will be expected to make significant contributions to the mathematical foundations of the programme, engage actively with the broader DataSıg II team, and participate in weekly collaborative meetings at Imperial-X or The Alan Turing Institute.  They will interact with DataSig’s scalable computation  objective of extending our RoughPy framework to support GPU/FPGA acceleration for real-time stream processing.

The successful candidates will play a central role in shaping the theoretical and computational tools that underpin the programme’s vision. If you are passionate about mathematics, machine learning, and making a real-world impact, we encourage you to apply and help shape the future of streamed data science.

What we are looking for:

The essential requirements for this post are as follows:

• Hold (or be near completion of) a PhD in Mathematics or a closely related field relevant to the Programme.
• Strong grounding in mathematical foundations relevant to the Programme, such as rough path theory, controlled differential equations, or stochastic analysis.
• Understanding of modern machine learning techniques, especially those related to streamed data, transformers, or LLMs.
• Ability to develop and apply new concepts.
• Creative approach to problem-solving.
• Ability to carry out original research and to produce published research papers.
• Ability to identify, develop and apply concepts, techniques and methods in new contexts.
• Strong computational and programming skills, including experience with numerical methods and algorithm development.

What we can offer you:

• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Grow your career with access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
• Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes).

Further Information

The position is fixed term for 24 months.

The expected start date is 1^st January or soon thereafter.

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range, £43,863 - £47,223 per annum.

In addition to completing the online application, candidates should attach:

• A full CV,
• A 2-page research statement describing why the candidate’s expertise is relevant to this position and future research plans; and
• The details of three referees.

For any specific queries regarding the post please contact:
Prof Thomas Cass, (thomas.cass@imperial.ac.uk).

If you experience any technical issues when applying online, please email:
(recruitment@imperial.ac.uk)

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