Wearables and Biosensors in Out-of-Hospital Diagnosis and Monitoring of Primary Aldosteronism (DC5)

This PhD project is embedded in Work Package 1: Hormone Dynamics of the ENDOTRAIN network and focuses on optimizing the diagnosis of primary aldosteronism using real-world, continuous physiological and hormonal data streams based on chronobiologic steroid rhythmicity and environmental challenges (i.e. salt intake). 

Key activities: 

• Leverage dynamic hormone profiling (e.g., U-RHYTHM) and next-generation biosensors for ambulatory assessment in patients with primary aldosteronism
• Conduct structured clinical phenotyping including endocrine diagnostics and monitoring parameters during low and high salt intake and during physiologic stressors of daily life
• Integrate wearable-derived physiological data (e.g., activity, heart rate, temperature) with endocrine test outcomes to identify diagnostic patterns
• Contribute to multimodal datasets feeding into the broader development of digital diagnostic tools in endocrinology. 

Research Fields: 

Endocrinology, Chronobiology, Digital Health, Medical Sensors, Systems Physiology, Internal Medicine 

Secondments: 

•  University of Ulm (D): To work with algorithms for wearable data
• University of Manchester (UK): To learn mathematical modelling of hormone rhythms.
• University of Bristol (UK): To learn mathematical modelling of hormone rhythms.  

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

The students will be enrolled in the structured PhD programme of the LMU Ph.D. Medical Research - Faculty of Medicine - LMU Munich 
 

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

We are seeking highly motivated candidates with: 

• A Master’s degree (MSc or equivalent) in Medicine, Biomedical Sciences, Physiology, Bioengineering, or a related field
• Strong interest in translational endocrinology and digital health technologies
• Basic programming or data science skills (R, Python) and interest in wearable data analysis are an asset
• Excellent command of written and spoken English
• Good communication skills and capacity for interdisciplinary collaboration 

Applicants must fulfill eligibility criteria for LMU Munich-based PhD positions and be willing to participate in training activities across Europe. 

• Competitive salary according to German Research Foundation (DFG) regulations
• Full social security coverage in Germany
• Travel and secondment budget included
• Opportunities for international networking, industry exposure, and career development 

Applications will only be accepted through the Jobbnorge portal.

Applications without the mandatory attachments (application, CV, mobility declaration, motivation templates) will not be considered.

Informal inquiries may be directed to Prof. Nicole Reisch and Prof. Martin Reincke (Nicole.reisch@med.uni-muenchen.de and martin.reincke@med.uni-muenchen.de)