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

At the University Heart and Vascular Center (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 including biobanking, structured follow-ups, and modern computer-assisted methods.

The German Research Foundation (DFG) has accepted Dr. med. Shinwan Kany into the prestigious Emmy Noether Programme. The newly established research project focuses on the topic "Risk stratification for atrial fibrillation and heart failure in individuals with rare cardiomyopathy gene variants using novel methods". The project aims to link large-scale epidemiological data, cloud infrastructures, and machine learning to develop predictive models for high-risk patients.

Your task:

• You develop, implement, and validate novel machine learning algorithms for the advanced automated analysis of multimodal cardiovascular datasets
• Your primary focus will be on training deep convolutional neural networks on 12-lead ECG waveforms to detect subtle subclinical electrophysiological signatures and derive individualized "AF-Risk Scores" and "HF-Risk Scores"
• In parallel, you will design and validate deep-learning-based semantic segmentation models for the automated extraction of structural cardiac endophenotypes from CINE MRI sequences within the UK Biobank
• You will deploy explainable artificial intelligence techniques (such as saliency maps) to visually localize and interpret the underlying prediction patterns of the ECG-AI models for clinical partners
• You will conduct genome-wide association studies (GWAS) and gene-based rare variant burden analyses (utilizing software frameworks like REGENIE) for the derived electrophysiological and structural intermediate traits
• You will collaborate closely with data managers and clinical researchers within the team, and prepare your scientific findings for publication in high-impact international journals

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

• Excellent Master’s degree or equivalent degree in Data Science, (Bio)Informatics, (Bio)Statistics, Computational Biology, or a closely related quantitative field
• Technical competence in Data Science and Data Engineering, demonstrated through an initial GitHub presence, academic work, or a comparable project portfolio
• Proficient handling of PyTorch as well as practical experience in processing 1D time series/biosignals (waveforms) or 2D image data
• Solid programming skills in languages relevant to data analysis, especially Python and/or R
• Genuine curiosity about clinical cardiovascular medicine, high intrinsic motivation, results-oriented work, as well as strong self-management skills
• A strong intrinsic drive to advance the translation of scientific findings into patient care and successfully complete your doctorate within the designated timeframe
• Excellent communication skills in both German and English; the ability to act as an effective bridge between technical and clinical partners

Preferred:

• Prior knowledge in the field of biosignal processing (e.g., digital ECG analysis, waveform processing) and/or medical image processing (e.g., U-Net-based segmentation)
• Initial contact with statistical genetics (e.g., quality control of GWAS data) or cloud-computing structures (e.g., DNAnexus)

Please apply with your CV, a motivation letter outlining your research interests in the project from both a technical (deep learning, ECG biosignal processing, image segmentation) and clinical perspective, reference projects demonstrating your technical excellence along with a description of your own contribution to them, and the contact details of preferably three researchers who have agreed to provide letters of reference.

• Fair and transparent compensation in accordance with our collective bargaining agreement (TVöD/VKA) (€ 63.600 - € 91.100), taking into account qualifications and professional experience. The salary range applies to a full-time position of 38.5 hours per week. The amounts listed are guidelines and do not constitute a salary guarantee.
• Targeted and individualized professional development at both the technical and project levels is provided, offering long-term prospects in a meaningful work environment
• Comprehensive continuing education and training programs at our UKE Academy for Education and Career
• Opportunities to help shape our “UKE INside” personnel policy through cross-functional and cross-hierarchical projects
• Sustainable commuting: Subsidies for the Deutschlandticket as a job ticket and Dr. Bike bicycle service
• Excellent health, prevention, and sports programs
• Family-friendly work environment: Partnerships for childcare, free vacation care, counseling for employees with family members requiring care
• A secure job, meaningful work, and a supportive team environment
• Structured onboarding and open knowledge sharing within the team
• Our employee restaurant offers a wide variety of culinary options; additional options are available at the “Health Kitchen” cafés and bistros and at a supermarket located directly on the premises

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.