Mathematical modelling of the cross-talk interactions between the HPA axis and the renin-angiotensin system (DC10)

Hormonal concentrations are regulated by endocrine axes and are the perfect example of complex regulatory systems involving multiple levels of organisation. Endocrine regulation is highly dynamic, with hormone levels exhibiting complex periodic behaviour over short and long timescales (e.g., hourly, daily and monthly rhythms). These systems also exhibit nonlinear responses to perturbations, typically mediated by feedback loops involving multiple components and crosstalk interactions with other endocrine systems (1, 2). At the same time, endocrine systems exhibit trade-offs between sensitivity and robustness, which allows adaptability to physiological challenges. Importantly, dysregulation of these dynamic processes can lead to disease. 

The PhD candidate will leverage multimodal datasets from dynamic hormone profiling (e.g., U-RHYTHM) (3) and biosensors for ambulatory assessment to develop mathematical models of the Hypothalamic-Pituitary-Adrenal axis and its cross-talk interactions with the renin-angiotensin system. 

The project aims are to:  

• Predict dynamic hormone profiles in healthy individuals and in patients with endocrine conditions (PA, MACS, PAI and CAH), 
• Predict dynamic responses to physio- pathological stimuli, from sleep disruptions to clinical tests such as dexamethasone suppression tests and responses to salt loading,
• Integrate hormonal and wearable device data (e.g., actigraphy, heart rate, temperature) with endocrine test outcomes to optimise diagnosis,
• Compute optimal dosing time points of hormonal replacement therapy,
• Contribute to the development of computer platforms that support the prevention, diagnosis and management of endocrine disease (endocrine digital twins), 

The PhD position is embedded in Work Package 3 (Trustworthy Data and Models) of the EU Horizon ENDOTRAIN doctoral training network. Participants will collaborate closely with other Doctoral Candidates and engage in secondments to technical and clinical partners within the consortium. 

1. E. Zavala et al., Trends Endocrinol. Metab. 30, 244–257 (2019). 

2. R. Bertram, Compr. Physiol. 5, 911–927 (2015). 

3. T. J. Upton et al., Sci. Transl. Med. 15, eadg8464 (2023). 

Research Fields 

Applied Mathematics, Computer Science, Endocrinology, Digital Health, Medical Sensors, Systems Physiology 

Secondments 

• University of Bristol (UK): Salt-dependent regulation of aldosterone secretion by ACTH and angiotensin II in healthy persons.
• Evangelismos General Hospital Athens (GR): New diagnostic algorithms for autonomous cortisol secretion (MACS, Cushing’s). 

The University of Manchester is the largest single-site university in the UK with around 38,000 students and more than 11,000 staff.  We are committed to expanding our world-leading research, and exploiting our capability for interdisciplinary research; transforming the way our students learn to make them the most employable graduates and truly global citizens; and ensuring that all our activities make a positive difference to society. The University of Manchester has been ranked the 35^th best university in the QS World University Rankings 2026, making it the 7^th best university in the UK. 

The student will be enrolled in the structured PhD programme at the Division of Diabetes, Endocrinology & Gastroenterology (DDEG), and in partnership with the Centre for Biological Timing (CfBT), the Department of Mathematics and the Institute for Data Science and AI at The University of Manchester. Housed within the CfBT, the University of Manchester has one of the largest groups of circadian biologists in Europe. Example research programmes include: molecular mechanisms within the body clock; the impact of light, environment and behaviour on our body clock, health, and wellbeing; circadian control of metabolism, inflammation and behaviour. The University of Manchester also offers a leading environment in applied mathematics, data science and AI. The PhD candidate will be based at the DDEG and benefit from access to world-leading expertise in endocrinology, state-of-the-art high performance computing facilities, multimodal datasets, wearable technologies, mathematical training, and world-leading international collaborations. 

The Faculty of Biology, Medicine and Health is comparable in size to a medium-sized UK university. Thirty undergraduate and 90 postgraduate programmes offer our students opportunities to develop the skills and knowledge they need for a successful career. The Faculty has an integrated structure, developed to deliver its key research and innovation goals (I) to undertake world-class discovery science, (II) to develop new approaches to prevention and early detection of disease, and (III) to develop the next generation of person-centred therapies. This structure facilitates interdisciplinary working and enables us to learn from each other and share best practice, articulate our research strengths, drive large-scale, collaborative research activities and strengthen relationships with our research and healthcare partners. The integration of discovery biology, clinical application and patient care within a single Faculty, particularly in a region with notable health inequality, provides us with a real opportunity to have a very significant and positive impact on people’s lives. Key partnerships in the charitable sector include British Heart Foundation; Cancer Research UK; Diabetes UK; and the Wellcome Trust; and the Faculty also has research and funding links to a number of commercial organisations including Unilever, AstraZeneca, GlaxoSmithKline and Boots, who will help us to bring new drugs and products to the market. 

The candidate should work full-time on the project and must not have resided or carried out their main activity (work, studies, etc.) in the UK for more than 12 months in the 36 months immediately before their recruitment date.  

We want to foster the next generation of innovators in digital endocrinology and support ambitious students to develop their full potential and reach the next level of their careers. During your PhD, you will be part of a team of interdisciplinary researchers spanning mathematics, computer science, bioengineering and endocrinology. As part of this project, you will also have access to an international collaborative network of world-leading experts in mathematical biomedicine, clinical endocrinology and chronophysiology. We value basic and translational research equally and are passionate about delivering transformative research that innovates and impacts positively upon people’s lives. Training opportunities on industry engagement, securing research funds, and Patient and Public Involvement and Engagement (PPIE) activities will be available. Applications from underrepresented groups in STEM subjects are strongly encouraged. 

Participation in the interdisciplinary training of the ENDOTRAIN network is mandatory, including workshops, retreats, transferable skills courses, and cohort-wide meetings across Europe. 

We are seeking a highly motivated candidate with: 

• A first-class degree in Mathematics, Physics, Bioengineering or a closely related discipline with a strong mathematical component (Masters level or equivalent),
• A solid background in ordinary and/or delay differential equations, model parameterisation, sensitivity analysis and optimisation,
• Excellent programming skills (Python, Matlab or Julia),
• Good dominion of time series analysis, dynamical systems theory and bifurcation analysis is 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. 

A funded scholarship is available for a EU or non-EU candidate in competition with all other PhD applications. The scholarship will cover tuition fees, training support, travel and secondments, and a stipend at standard rates for 3-3.5 years. Full national healthcare coverage in the United Kingdom. The candidate will also have access to opportunities for international networking, industry exposure, and career development 

Applications will be run through the University of Manchester's recruitment site. See link above when active.

Informal enquiries should be addressed to Dr Eder Zavala via email: eder.zavala@manchester.ac.uk