PhD Research Fellow in Computational Biology – Scientific Machine Learning for Endocrinology University of Bergen in Norway

The University of Bergen invites applications for a PhD Research Fellow in Computational Biology, based in the Department of Informatics. This position is part of the Mathematical Systems Biology group within the Computational Biology Unit (CBU), a cross-departmental research environment at UiB that brings together expertise in bioinformatics, biology, mathematics, computer science, chemistry, and biomedicine. The CBU focuses on developing and applying novel computational methods to address fundamental biological questions.

The PhD project centers on leveraging Scientific Machine Learning (SciML) to improve modelling and simulation of complex systems in endocrinology. Digital endocrinology is an emerging interdisciplinary field that integrates technology into the diagnosis, management, and treatment of hormone-related disorders, moving from episodic assessments to continuous, real-time monitoring and personalized care. The research will develop methods for real-time prediction of quasi-periodic hormone profiles and early disease signal detection, combining mechanistic modelling with machine learning to enhance inverse modelling and parameter estimation.

The successful candidate will join a vibrant research community and benefit from membership in the new Norwegian Research School for Computational Life Sciences (CompLiNOR), launching in autumn 2026. The position is funded by the University of Bergen and offers a professionally stimulating environment, a gross annual salary of NOK 568,700, enrolment in the Norwegian Public Service Pension Fund, and welfare benefits. The fellowship is for 3 years, with the possibility of a 4th year involving career-promoting work such as teaching, depending on departmental needs and candidate qualifications.

Applicants must hold a master's degree or equivalent in Mathematics, Computational Sciences, Physics, or a closely related discipline with a strong mathematical/computational component. Master students may apply if they complete their final master exam before 30.06.2026. Required skills include programming (Python, Matlab, or Julia), mathematical modelling (especially ordinary and/or delay differential equations), and experience with machine learning and neural networks. Additional advantages include experience with model parameterisation, sensitivity analysis, optimisation, time series analysis, dynamical systems theory, bifurcation analysis, and interest in translational endocrinology and digital health technologies. Excellent command of written and spoken English is required, and applicants must provide documentation of English proficiency if needed.

Applications must be submitted via the Jobbnorge portal and include a CV, motivation letter, transcripts, diplomas, certificates, references, documentation of English proficiency, and a publication list. All documents should be translated into English or a Scandinavian language. For further information, contact Professor Susanna Röblitz ([email protected]) or Head of Department Inge Jonassen ([email protected]). The University of Bergen is committed to diversity and inclusivity, encouraging applicants from all backgrounds to apply. The application deadline is 17 May 2026.