Eder Zavala

The University of Manchester is recruiting a PhD student to join its Mathematical Biomedicine Group through an international strategic partnership with the University of Bergen in Norway. This project investigates whether mathematical modelling can help personalise hormone replacement therapies for people living with Addison's disease. Conventional cortisol replacement treatments can struggle to reproduce the natural daily rhythms of this essential hormone. The research will explore personalised endocrine chronotherapies by combining mechanistic modelling, computational optimisation and high-resolution human hormone data. The doctoral researcher will develop models of hormonal dynamics and transport across human tissues, analyse high-resolution endocrine time series, and optimise drug-delivery strategies for individual patients. The work sits at the interface of applied mathematics, computational biology and clinical endocrinology, with opportunities to collaborate with researchers and clinicians across an international network. The student will be based in the Mathematical Biomedicine Group at the University of Manchester and will be co-supervised by Professor Susanna Röblitz and Professor Marianne Øksnes at the University of Bergen. The project includes regular research visits to Norway and opportunities to engage with collaborators in Bristol and at Karolinska Institutet. This is a collaborative research environment focused on quantitative approaches to biological and medical challenges in endocrine health.

📢 The University of Manchester is recruiting a Postdoctoral Research Associate in Mathematical Biomedicine to join Eder Zavala’s group. The project is funded through a UKRI Future Leaders Fellowship and focuses on digital endocrinology , using mathematical and computational approaches to study circadian rhythms , hormonal time-series data, and wearable technologies. The successful candidate will investigate how rhythms become misaligned and help translate these insights into personalised approaches for diagnosing and managing endocrine conditions. Research methods include time-series and network analysis , Bayesian inference , machine learning , parameter estimation , high-performance computing , and mathematical modelling using differential equations . Applicants should have strong scientific programming skills in Python, Julia, R and/or MATLAB . Experience with dynamical systems and modelling with ODEs or DDEs is especially valuable. The role is interdisciplinary and involves collaboration with PhD researchers, clinicians, mathematicians, and computer scientists in the UK and internationally. Location: University of Manchester, United Kingdom Duration: Full time, 1 February 2027 to 31 December 2029 Deadline: 23 October 2026 Apply: Use the application link provided in the post.