Up to 30% off — ends 7 Aug
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Up to 30% off — ends 7 Aug
ONLY00h00m00s
Zuowei Wang
5 months ago
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Fully Funded PhD Position: Mathematical Modelling of Adrenal Gland Steroid Biosynthesis (DC12) – ENDOTRAIN MSCA Doctoral Network University of Reading in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Expired
Country
United Kingdom
University
University of Reading

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About this position
The University of Reading is offering a fully funded PhD position in Mathematical Modelling of Adrenal Gland Steroid Biosynthesis (DC12) as part of the prestigious ENDOTRAIN MSCA Doctoral Network. This three-year doctoral project is embedded within Work Package 3: Trustworthy Data and Models of the EU Horizon ENDOTRAIN network, focusing on the development and application of advanced mathematical modelling techniques to study the dynamics of adrenal gland steroid biosynthesis and their spatial relationship with adrenal tumours, particularly in the context of Primary aldosteronism (PA) and Mild autonomous hypercortisolism (MACS).
The successful candidate will develop spatiotemporal models to describe enzyme-mediated steroid synthesis in the cortex of the adrenal gland, relevant for the diagnosis of unilateral and bilateral PA and MACS. The project will build on both existing and new imaging data provided by partner groups within the ENDOTRAIN network. Key objectives include:
- Developing reaction-diffusion mathematical models of steroid enzyme-mediated synthesis and implementing these into numerical simulation codes to handle complex spatial profiles.
- Validating models by comparing analytical and numerical predictions with experimental data.
- Providing quantitative insights into the variation of corticoids and androgens within the adrenal cortex.
- Quantifying the impact of pathway signalling dysregulation and spatial disturbances (such as tumours) on hormone expression levels.
- Contributing to the development of computer platforms for the prevention, diagnosis, and management of endocrine diseases (endocrine digital twins).
The project offers extensive collaboration opportunities, including secondments to technical and clinical partners such as Evangelismos General Hospital Athens, Ludwig-Maximilians-Universität München, and the University of Manchester. The candidate will benefit from interdisciplinary training, workshops, retreats, and cohort-wide meetings across Europe, as well as access to state-of-the-art high performance computing facilities and international collaborations at the University of Reading's Department of Mathematics & Statistics.
Eligibility and Requirements: Applicants must hold a Master’s degree (or equivalent) in Mathematics, Physics, Bio- or Biomedical Engineering, or a closely related discipline with a strong mathematical component. Essential skills include mathematical modelling, differential equations, dynamical systems, numerical analysis, and programming (Python, Matlab, Fortran, or C/C++). Experience with numerical solutions of differential equations and knowledge of statistics and probability are desirable. Candidates must not have resided or carried out their main activity in the UK for more than 12 months in the 36 months prior to recruitment. Excellent English language and communication skills are required.
Funding and Benefits: The position is fully funded for three years, with a gross annual salary ranging from £42,978 to £46,974 (depending on eligibility for the family allowance), plus living and mobility allowances. A travel and secondment budget is included, along with opportunities for international networking, industry exposure, and career development.
Application Process: Applications must be submitted via the Jobbnorge portal with all mandatory attachments. For further details, visit the project page and the Department of Mathematics & Statistics at the University of Reading.
This is an exceptional opportunity for a highly motivated candidate to contribute to cutting-edge research at the intersection of mathematics, biomedical engineering, and endocrinology, within a vibrant international doctoral network.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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