PhD position at the University of Reading, UK (ENDOTRAIN) (DC12)
Deadline: 15.02.2026
Publisert
The University of Reading (UREAD) is a leading research institution set in beautiful, award-winning parkland with London Paddington less than 30 minutes away by train. It offers leading environment in applied mathematics, data and computer sciences, and biomedical engineering.
The PhD candidate will be based at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/), which has a long and established track record of research with 98% of research outputs ranked as world leading or internationally excellent, and benefit from state-of-the-art high performance computing facilities, mathematical training, and world-leading international collaborations.
PhD position
There is a vacancy for a PhD Research Fellow in Mathematical Modelling of Adrenal Gland Steroid Biosynthesis (DC12) at the University of Reading, UK. The position is funded by the European Commission through the MSCA Doctoral Network Endotrain (Grant No: 101227148) and coordinated by the University of Bergen, Norway.
19 PhD Fellowships available in Digital Endocrinology in the Marie Skłodowska-Curie Doctoral Network (ENDOTRAIN).
Join Europe’s first doctoral network in digital endocrinology – integrating AI, sensor technology, omics, and clinical medicine to transform diagnosis and treatment of adrenal diseases.
Digital medicine is entering a new era where human “digital twins” and sensor-based monitoring allow personalised diagnosis and treatment. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal disorders as a case study for advancing digital health in Europe.
This PhD project is embedded in Work Package 3: Trustworthy Data and Models of the EU Horizon ENDOTRAIN doctoral training network and aims to apply mathematical modelling methods to study adrenal gland steroid biosynthesis dynamics and their spatial relationship with adrenal tumours found in Primary aldosteronism (PA) and Mild autonomous hypercortisolism (MACS). Spatiotemporal models will be developed to describe enzyme-mediated steroid synthesis in the cortex of an adrenal gland relevant for diagnosis of unilateral and bilateral PA and MACS building on existing and new imaging data obtained by partner groups in the ENDOTRAIN network.
The objectives of the project include:
Developing reaction-diffusion mathematical description of steroid enzyme mediated synthesis in the cortex of a healthy adrenal gland and implementing them into numerical simulation codes for handling complicated spatial profiles.
Validating the models by comparing their analytical and numerical predictions with available experimental data.
Applying the developed models to provide quantitative understanding of how the spatiotemporal profile of corticoids and androgens varies within the cortex region of a healthy adrenal gland.
Quantifying the effect that pathway signalling dysregulation in different zones of the cortex has on expression levels of corticoids and androgens.
Providing quantitative understanding of the impact of spatial disturbances (e.g., tumours) in the different zones of the cortex tissue on dynamic corticoid and androgen expression levels.
Contributing to the development of computer platforms that support the prevention, diagnosis and management of endocrine disease (endocrine digital twins),
Participants will collaborate closely with other Doctoral Candidates and engage in secondments to technical and clinical partners within the consortium.
Research Fields
Applied Mathematics, Computer and Data Sciences, Biomedical and Chemical Engineering, Endocrinology, Digital Health, Medical Sensors, Systems Physiology
Secondments
Evangelismos General Hospital Athens (GR) and Ludwig-Maximilians- Universität München (DE): Collect data on MACS and PA patients, respectively
University of Manchester (UK): Inform mathematical model development and parameterisation and test model outcomes for PA and MACS using available experimental data
Qualifications and personal qualities:
We are seeking highly motivated candidates with:
A Master’s level or equivalent degree in Mathematics, Physics, Bio- or Biomedical engineering, or a closely related discipline with a strong mathematical component
A solid background in mathematical modelling, ordinary and partial differential equations, dynamical systems, and numerical analysis
Excellent programming skills (e.g., Python, Matlab, Fortran or C/C++)
Experience in numerical solutions of differential equations and knowledge of statistics and probability are desirable
Strong interest in translational endocrinology, wearable device data and digital health technologies
Excellent command of written and spoken English and communication skills (oral and written).
Applicants must fulfil eligibility criteria for UK-based PhD positions and be willing to participate in training activities across Europe.
The salary includes a living allowance, a mobility allowance and if eligible a family allowance. Thus, the gross salary will range from £42,978 - £46,974 (depending on eligibility for the family allowance) per annum. This is gross pay per year before taxes and other deductions are made.
Three years duration
Travel and secondment budget included
Opportunities for international networking, industry exposure, and career development
The University of Reading (UREAD) is a leading research institution set in beautiful, award-winning parkland with London Paddington less than 30 minutes away by train. It offers leading environment in applied mathematics, data and computer sciences, and biomedical engineering. The PhD candidate will be based at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/), which has a long and established track record of research with 98% of research outputs ranked as world leading or internationally excellent, and benefit from state-of-the-art high performance computing facilities, mathematical training, and world-leading international collaborations.
Application procedure
All applications must be submitted via the Jobbnorge portal
Your application must include the mandatory attachments from the ENDOTRAIN webpages - including "1. Application form" - "2. CV" - "3. Mobility declaration" - "4. Motivation Letter"
Eligibility (MSCA Doctoral Network rules)
Applicants can be of any nationality.
Must not have resided or carried out a main activity in the host country for more than 12 months in the past 36 months before start of the PhD.
Must hold a master’s degree (or equivalent) enabling doctoral studies.
Must not already hold a doctoral degree.
English proficiency required - transcripts of diplomas in English must be uploaded in Jobbnorge.
In the "Jobbnorge-CV": Only fill in the basics of your 1) personal details, 2) short information about your degrees (in the field "Education / academic qualifications") - in order to minimise repetition with the CV attachment.
It is a condition of employment that the master's degree has been awarded (documentation must be provided). If you have not yet completed your master's degree, you can apply provided completion of the final master exam before the position start date. Please submit a statement from your institution confirming the expected date of award of your master's degree.
For HR related questions contact the host institutions for the position you are applying.
For questions about the ENDOTRAIN programme, please contact Programme Manager Elizabeth Farmer (elizabeth.farmer@uib.no)
For HR-related questions, please contact HR-adviser Selina Hausberg (selina.hausberg@uib.no)
Diversity and inclusion
MSCA -Endotrain has a gender equality plan where gender balance among employees is therefore a goal. We encourage women to apply. If multiple applicants have approximately equivalent qualifications, the rules pertaining to moderate gender quotas shall apply. It is also a goal to recruit people with immigrant backgrounds. People with immigrant backgrounds and people with disabilities are encouraged to apply for the position.
Information about applicants may be made public even if the applicant has asked not to be named on the list of persons who have applied. The applicant must be notified if the request to be omitted is not met.
About MSCA Doctoral Networks
The MSCA Doctoral Networks aim to train creative, entrepreneurial, innovative and resilient doctoral candidates, able to face current and future challenges and to convert knowledge and ideas into products and services for economic and social benefit. The MSCA Doctoral Networks raise the attractiveness and excellence of doctoral training in Europe. Read More about the MSCA Doctoral Networks.
