Location: | Egham |
---|---|
Salary: | £40,839 per annum (including London Allowance) |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 9th July 2025 |
---|---|
Closes: | 14th August 2025 |
Job Ref: | 0725-151 |
Full-Time, Fixed-Term (18 months)
Salary is £40,839 per annum (including London Allowance)
Applications are invited for the post of Postdoctoral Research Associate in the Department of Mathematics for 18 months, starting 1st October 2025.
We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based on autofluorescence (AF) imaging and Raman spectroscopy for detection of metastatic lymph nodes during breast cancer surgery.
Engaging with and reporting to Dr Alexey A. Koloydenko (Department of Mathematics), the post holder will interact with researchers in statistics and machine learning at Royal Holloway, the Biophotonics Group at the University of Nottingham, clinicians at the Nottingham Breast Institute and RiverD International.
The successful candidate will develop and test new methods for detecting metastatic lymph nodes based on their molecular signatures as captured by AF and Raman spectroscopy. The project offers a statistician or mathematician an excellent opportunity for interdisciplinary training in biomedical and biophysics applications of mathematics, statistics and machine learning under real life constraints of clinical integration/validation and healthcare regulatory translation/commercialisation.
The position is part of the project `Integrated autofluorescence-Raman spectroscopy (AF-Raman) for intra-operative assessment of sentinel lymph node biopsies in breast cancer surgery' led by Prof. Ioan Notingher (Nottingham) and funded by the National Institute for Health and Care Research (NIHR).
Applicants will have a strong first degree and will also have or be close to completing a PhD in any of the following areas and the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying machine learning to real life problems, using Matlab, and familiarity with topological and geometric data analyses. Candidates will have excellent communication skills, enabling them to engage with the entire research group, presenting research results, and writing research articles.
In return, we offer:
Our highly competitive rewards and benefits package includes:
The post is based in Egham, Surrey where the University is situated in a beautiful, leafy campus near to Windsor Great Park and within commuting distance from London.
For an informal discussion about the post, please contact:
Dr Alexey Koloydenko on alexey.koloydenko@rhul.ac.uk
For queries on the application process the Human Resources Department can be contacted by email at: recruitment@rhul.ac.uk
Please quote the reference: 0725-151
Closing Date: 14 August 2025
Interview Date: 29 August 2025
Royal Holloway is committed to equality and diversity and encourages applications from all sections of the community.
Type / Role:
Subject Area(s):
Location(s):