PhD student (all genders) in Digital Cardiovascular Research at the University Heart & Vascular Center

At the University Heart and Vascular Centre (UHZ) of the University Medical Center Hamburg-Eppendorf (UKE), we redefine cardiovascular research by embedding large-scale clinical and translational science directly into our everyday clinical care. Our ecosystem combines deeply phenotyped cohort studies with more than 10,000 participants, comprehensive biobanking, longitudinal follow-up, and patient-centred research enabled by remote monitoring and connected wearables. We lead and contribute to multinational trials that shape clinical guidelines.

AF-B-STEP is a newly launched EU-IHI consortium co-ordinated by our centre. It tackles one of the most consequential open questions in arrhythmia research: how atrial fibrillation burden should inform diagnosis, risk stratification, and treatment – with direct relevance for FDA and EMA regulatory decisions. The consortium unites 18 partners from academia, industry, and patient organisations across Europe and Canada, integrating data from 60+ clinical trials and 500,000 patients. More at afburden.org.

Your role. You develop novel computational methods at the intersection of clinical data science and cardiovascular epidemiology – embedded in the creation of AF-BOLD, the consortium's landmark individual patient data meta-analysis combining 200,000+ patient-years of outcome data from 60+ trials. You design AI-driven approaches for harmonising heterogeneous clinical datasets – structured records, cardiac device remote-monitoring exports, digital ECGs, and wearable time series – and design quality assurance and anomaly detection pipelines for large-scale longitudinal patient data. You conduct analyses from this unique resource, contribute to integrating multimodal data into unified frameworks for machine learning and statistical modelling, and collaborate daily with clinical researchers, epidemiologists, and data engineers from across the consortium. This is a unique setting to build deep technical expertise while working on data and questions that directly shape patient care and regulatory decisions.

This position  (65% of the regular weekly working hours) is a fixed-term position for an initial period of three years in accordance with the WissZeitVG. An extension is anticipated.

The position is specifically designed as a training position with the opportunity to pursue a doctorate within the framework of the UKE’s PhD program.

• Excellent Master’s degree in Data Science, (Bio)Informatics, (Bio)Statistics, or a closely related quantitative field
• Technical excellence in Data Science and Data Engineering, demonstrated through an active GitHub profile, peer-reviewed publications, or a comparable project portfolio
• Proficiency in PyTorch, combined with hands-on experience in developing modern microservice- and API-based software while adhering to high software quality standards
• Solid experience working with relational databases (e.g., PostgreSQL), object storage (e.g., MinIO), and version control systems, including CI/CD pipelines with Git and GitLab
• Genuine curiosity about clinical cardiovascular medicine, intrinsic motivation, and a highly results-oriented mindset, and you should possess strong self-management skills. You can articulate and demonstrate all of these in your cover letter and interview.
• A strong intrinsic drive to advance the translation of scientific findings into clinical practice and patient care
• Excellent communication skills in both German and English; the ability to act as an effective bridge between technical and clinical partners

Preferred:

• Experience in analysing data from prospective or randomized clinical trials, ideally within cardiovascular medicine
• Familiarity with clinical trial data standards (e.g., CDISC SDTM/ADaM) and/or medical ontologies (e.g., SNOMED CT, LOINC)
• Demonstrable practical experience in applying and developing NLP- and/or LLM-based methods for information extraction from medical texts
• Proven hands-on experience in administering Linux-based research infrastructures, managing Kubernetes for microservice architectures, and workload automation

Please apply with your CV, a motivation letter outlining your research interests in the project from both a technical and clinical perspective, reference projects demonstrating your technical excellence and a description of your own contribution to them, and the contact details of preferably three researchers who agreed to provide letters of reference.

• Attractive compensation according to TVöD/VKA
• Secure employment with meaningful work and respectful collaboration
• Comprehensive onboarding and open knowledge exchange within the team
• Extensive training and further education programs at our UKE Academy for Education and Careers
• Opportunities to contribute to our “UKE INside” personnel policy through cross-professional and cross-hierarchical projects
• Sustainable travel: subsidies for the Deutschlandticket as a job ticket, and Dr. Bike bicycle service
• Family-friendly working environment: cooperation on childcare, free vacation childcare, advice for employees with relatives in need of care
• Excellent health, wellness, and sports programs
• A wide range of dining options in our staff restaurant, with additional choices available at the “Health Kitchen” cafés, bistros, and an on-site supermarket

We live diversity and value variety

We offer a work environment that provides equal opportunities regardless of age, gender, sexual identity, disability, ethnic and social origin, or religion. This is confirmed by our accession to the Charter of Diversity. We explicitly aim to increase the proportion of women in management positions, especially among scientific personnel in research and teaching. Women with equal qualifications will be given priority. The same applies in the case of under-representation of one gender in the advertised area. Persons with severe disabilities with equal aptitude, competence, and professional performance will be given priority.

> Learn more about "Diversity at UKE" here.