The University of Bergen, Faculty of Medicine, invites applications for a full-time PhD Research Fellow position in Optimized Monitoring of Patients with Primary Adrenal Insufficiency (DC1), as part of the ENDOTRAIN Doctoral Network. This three-year position, with possible extension, is embedded in Work Package 1 of the ENDOTRAIN network, which focuses on digital endocrinology and the development of advanced monitoring tools for adrenal diseases. The project is funded by the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie framework.

The research aims to investigate endocrine rhythms in patients with primary adrenal insufficiency (PAI) using real-world, continuous data streams. The project will analyze how cortisol levels affect tissue glucose, blood pressure, and sleep, correlating these findings with patient-reported outcomes. The ultimate goal is to define the optimal range of tissue cortisol in PAI and establish time-in-range metrics compared to healthy subjects.

Key project activities include a case-control study collecting wearable-based physiological data and hormone profiles from both healthy subjects and PAI patients at varying hydrocortisone doses. The research integrates wearable-derived data (blood pressure, tissue glucose, activity, heart rate, sleep) with 24-hour dynamic hormone profiling, proteomics, and patient-reported data. The candidate will contribute to multimodal datasets that support the development of digital diagnostic tools in endocrinology. The position offers secondments with technical and clinical partners, including the University of Ulm (algorithm development for wearable data) and the University of Manchester (mathematical modelling of hormone rhythms).

The successful candidate will join the Endocrine Medicine Research Group at the Department of Clinical Science, University of Bergen, and collaborate closely with Haukeland University Hospital. The research group comprises clinical researchers, molecular biologists, geneticists, and bioinformatics experts, providing a dynamic and interdisciplinary environment. Facilities include state-of-the-art biobanking, wearable technologies, hormone analytics, and extensive international collaborations.

Eligibility requirements include a master’s degree in medicine (MD), strong interest in translational endocrinology and digital health, and basic programming or data science skills (R, Python). Experience in relevant research projects is advantageous. Candidates must be fluent in English and able to work independently and collaboratively. Applicants must not have resided or worked in Norway for more than 12 months in the 36 months prior to recruitment. Those with foreign degrees must provide certified translations and a review from the Norwegian Directorate for Higher Education and Skills (HK-dir) confirming equivalence to a Norwegian master’s degree. Exemptions apply for Nordic and EEA medical graduates with Norwegian licensure.

The position offers a competitive salary (NOK 570,000–605,000 depending on qualifications), enrolment in the Norwegian Public Service Pension Fund, occupational injury insurance, full salary during sick leave for up to 52 weeks, paid parental leave, and free Norwegian language courses. The successful candidate will participate in the structured PhD programme at the Faculty of Medicine and benefit from interdisciplinary training, workshops, retreats, and cohort-wide meetings across Europe.

To apply, prepare all required documents (application form, CV, mobility declaration, motivation letter, transcripts) and submit them via the Jobbnorge electronic recruiting system. If your master’s degree is pending, include a statement of expected completion date. For further details, visit the ENDOTRAIN and University of Bergen webpages. The application deadline is 15th February 2026, and the position is scheduled to start in August 2026.

This opportunity is ideal for candidates seeking to advance their expertise in clinical endocrinology, digital health, and translational research within a leading European research environment.