Susanna Röblitz

The University of Bergen is offering a fully funded PhD position as part of the ENDOTRAIN MSCA Doctoral Network, focusing on the mathematical modelling of sex-differences in the human adrenal cortex and its associated disorders. This project, embedded in Work Package 3: Trustworthy Data and Models, aims to advance computational approaches for optimizing glucocorticoid replacement therapies in female patients with adrenal hormone deficiency, with a particular emphasis on maintaining or restoring fertility. The research will leverage multimodal datasets, including dynamic hormone profiling and biosensor data, to develop sophisticated mathematical models of the Hypothalamic-Pituitary-Adrenal (HPA) axis and its interactions with the Hypothalamic-Pituitary-Ovarian (HPO) axis. Key objectives include constructing models to delineate cross-talk mechanisms between the HPA and HPO axes, calibrating these models with wearable device data and hormone profiles from both healthy subjects and patients, characterizing variability in model parameters to generate virtual patients, and predicting dynamic hormone profiles and responses to therapy. The project also aims to contribute to the development of digital platforms for endocrine disease management, such as endocrine digital twins. The successful candidate will collaborate with other doctoral candidates and participate in secondments at Sapienza University of Rome (AI-based virtual twins) and LMU University Hospital Munich (model calibration). The position is hosted at the Department of Informatics, University of Bergen, within the Computational Biology Unit (CBU), a cross-disciplinary research environment with expertise spanning bioinformatics, biology, mathematics, computer science, chemistry, and medicine. The candidate will benefit from access to high-performance computing facilities, multimodal datasets, computational training, and international collaborations. Applicants must hold a master's degree or equivalent in a relevant discipline with a strong mathematical/computational component. Programming proficiency in Python, Matlab, or Julia is required, along with a solid background in mathematical modelling. Experience in model parameterisation, sensitivity analysis, optimisation, time series analysis, dynamical systems theory, and bifurcation analysis is advantageous. Candidates should demonstrate strong interest in translational endocrinology, wearable device data, and digital health technologies, as well as excellent communication skills and the ability to work both independently and collaboratively. Proficiency in English is essential. The position offers a gross annual salary of NOK 570,000, full social security coverage, travel and secondment budget, and opportunities for international networking and career development. Participation in the interdisciplinary training of the ENDOTRAIN network is mandatory, including workshops, retreats, and cohort-wide meetings across Europe. Applicants must not have resided or carried out their main activity in Norway for more than 12 months in the 36 months immediately before recruitment. Applications are accepted exclusively through the Jobbnorge portal, with all mandatory attachments required by the deadline of February 15, 2026. For further details, visit the Computational Biology Unit at https://cbu.w.uib.no/ and the official FindAPhD posting here .

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.