Data Integrity for Digital Health & Medical Wearables (DC9)

Remote clinical trials, powered by continuous data from medical wearables, promise to unlock new insights into complex diseases. However, integrating and synchronizing diverse, high-volume datasets, from dynamic hormone profiles to wearable biosensors (heart rate, actigraphy, temperature), is a significant hurdle. Data quality loss is manifold, threatening the validity of groundbreaking medical discoveries 

Your Mission: Architecting Data Integrity and Workflows for Endocrine Digital Twins

As a PhD candidate, your goal is to ensure the integrity, synchronization, and seamless integration of this vital multimodal data. You will be at the forefront of developing the automated, robust, and scalable infrastructure required for advanced analysis and modeling. 

  Key Project Aims – Your Roadmap to Innovation: 

•     Data Platform Creation: Design and maintain a state-of-the-art platform to seamlessly integrate complex hormonal data, high-resolution wearable sensor streams, and endocrine test outcomes. 
•  Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms to automatically identify, flag, and mitigate data artifacts and quality issues in real-time. 
• Supporting Digital Twins: Play a crucial role in developing the next generation of computer platforms that support the prevention, diagnosis, and management of endocrine diseases. 

You will be embedded in Work Package 2: Technologies for Multimodal Data of ENDOTRAIN, collaborating closely with an international network of clinical and technical experts across the ENDOTRAIN consortium. This includes mandatory secondments to maximize your practical exposure and network. 

Research fields: 

Health Informatics, Biomedical Engineering, Computer Science, Endocrinology, Digital Health, Medical Sensors, Cyber-physical Systems.  

Secondments:

• University of Rome (I): AI-based virtual twins for monitoring, disease classification, and decision support in clinical practice
• Leitwert AG (CH): Health middleware 

The PhD position is based at the Institute of Biomedical Engineering at the University of Ulm, Germany. 

We Offer You: 

•     A World-Class Environment: Access to a leading research environment specializing in hardware/software for medical wearables, translational endocrinology, and machine learning for medical time-series. 
•    Cutting-Edge Resources: Benefit from state-of-the-art High-Performance Computing (HPC) facilities, unique multimodal datasets, and advanced wearable technologies. 
•    Global Collaboration: Extensive technical and physiological training, and the opportunity to build a professional network through world-leading international collaborations. 

Join us to translate complex biomedical data into actionable clinical intelligence and shape the future of personalized medicine! 

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.  

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

We are seeking a highly motivated candidate with: 

• A first-class degree in Electrical, Biomedical, or Communications Engineering,  Computer or Data Science or a closely related discipline with a strong mathematical and data management component (Master’s level or equivalent),
• A solid background in signal processing and machine learning
• Knowledge of embedded systems, cloud and edge computing is an advantage
• Excellent programming skills (Python, Matlab or C),
• Good dominion of biomedical signals and human physiology is desirable,
• Strong interest in translational endocrinology and digital health technologies
• Excellent command of written and spoken English and communication skills (oral and written). 

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

A funded scholarship is available for a EU or non-EU candidate in competition with all other PhD applications. 

The scholarship will cover tuition fees, training support, travel and secondments, and a stipend at standard rates for 3 years. Salary range (gross): 55'000 euros/year 

The candidate will also have access to 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 enquiries should be addressed to Prof. Walter Karlen via email: bmt@uni-ulm.de