Postdoctoral Research Associate
| Dyddiad hysbysebu: | 08 Gorffennaf 2025 |
|---|---|
| Cyflog: | £40,839 bob blwyddyn |
| Gwybodaeth ychwanegol am y cyflog: | including London Allowance |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 07 Awst 2025 |
| Lleoliad: | Egham, Surrey |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | Royal Holloway University of London |
| Math o swydd: | Cytundeb |
| Cyfeirnod swydd: | 0725-151 |
Crynodeb
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 adapt existing and 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). The aim of this project is to build an instrument, leveraging statistical and machine learning techniques, to allow surgeons to examine the sentinel lymph nodes during the first surgery, while the patient is still in the operating room, and if necessary, remove the lymph nodes in the armpit without delay. This will improve patient care as currently positive lymph nodes are detected by histology, requiring 1-2 weeks and sometimes resulting in the need for patients to return for a second surgery for axillary node clearance.
Applicants will have a strong first degree and will also have or be close to completing a PhD in any of the following areas as well as 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 statistical and machine learning to real life problems, using a popular computer language (e.g. Matlab, Python), 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:
-Access to a world-class research environment
-Opportunities to produce high-quality publications
-Development of multidisciplinary skills in statistical modelling, machine learning, AF imaging and Raman spectroscopy and clinical translation of automated biophotonics technologies
-Collaboration opportunities with internationally leading researchers in biophotonics, machine learning and breast cancer surgery, as well as companies interested in our project results and partnering in spin-off initiatives
-Travel opportunities to visit research partners and attend conferences.
Our highly competitive rewards and benefits package includes:
-Generous annual leave entitlement
-Training and Development opportunities
-Pension Scheme with generous employer contribution
-Various schemes including Cycle to Work, Season Ticket Loans and help with the cost of Eyesight testing.
-Free parking
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
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 adapt existing and 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). The aim of this project is to build an instrument, leveraging statistical and machine learning techniques, to allow surgeons to examine the sentinel lymph nodes during the first surgery, while the patient is still in the operating room, and if necessary, remove the lymph nodes in the armpit without delay. This will improve patient care as currently positive lymph nodes are detected by histology, requiring 1-2 weeks and sometimes resulting in the need for patients to return for a second surgery for axillary node clearance.
Applicants will have a strong first degree and will also have or be close to completing a PhD in any of the following areas as well as 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 statistical and machine learning to real life problems, using a popular computer language (e.g. Matlab, Python), 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:
-Access to a world-class research environment
-Opportunities to produce high-quality publications
-Development of multidisciplinary skills in statistical modelling, machine learning, AF imaging and Raman spectroscopy and clinical translation of automated biophotonics technologies
-Collaboration opportunities with internationally leading researchers in biophotonics, machine learning and breast cancer surgery, as well as companies interested in our project results and partnering in spin-off initiatives
-Travel opportunities to visit research partners and attend conferences.
Our highly competitive rewards and benefits package includes:
-Generous annual leave entitlement
-Training and Development opportunities
-Pension Scheme with generous employer contribution
-Various schemes including Cycle to Work, Season Ticket Loans and help with the cost of Eyesight testing.
-Free parking
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
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