At the University Medical Center Hamburg-Eppendorf (UKE), we are committed to excellence in research, education, and comprehensive healthcare across our clinics. Every day, our team of approximately 17,000 dedicated employees works to make the world a healthier place. Our goal is to be one of the leading university hospitals while also being the best employer in our industry.
At UKE, we believe that meaningful and successful work should align with our employees' personal needs and individual lifestyles. Just as diverse as these needs are, so too is the variety of personalized solutions we offer.
Welcome to the UKE.
- Job-ID: J000006920
- Contract Type: Temporary
- Employment Type: Full time/ Part time
- Closing Date: 05.10.2026
- Organization: UKE_Zentrum für Geburtshilfe, Kinder- u. Jugendmedizin
- Category: Research & Science
- Department: Klinik für Pädiatrische Hämatologie und Onkologie
Main tasks
The Research Institute Children's Cancer Centre at the University Medical Center Hamburg-Eppendorf is looking for a highly motivated research assistant (PhD student) in the Computational Pediatric Oncology working group (headed by Prof. Dr. Michael Bockmayr) starting 01.11.2026. A later start can be accomodated in principle. We actively support and offer the chance to pursue a PhD alongside the project.
This position is part of a BMFTR-funded Junior Research Consortium conducted in close cooperation with the TU Berlin (Machine Learning Group/Dr. Mina Jamshidi Idaji) and the LMU München (Computational and Molecular Pathology/Prof. Dr. Philipp Jurmeister). The project focuses on developing novel ML methods for multimodal learning in computer-aided diagnostics. The goal is to integrate histopathological, clinical, and molecular data to optimize AI-based decision-making tools in oncology.
Strong individualized support is guaranteed throughout the entire period. In addition, you can expect a motivated and dynamic team of physicians, natural scientists, bioinformaticians, technical assistants, and students at the Research Institute, who are investigating pediatric cancers as part of various projects and with different approaches.
Your tasks:
- Development and evaluation of clinically relevant multimodal classification algorithms using machine learning methods based on image data and high-dimensional omics datasets
- Integration of histological, molecular (genomics, epigenomics, transcriptomics at the bulk and single-cell levels), and clinical data
- Close collaboration with partners and other research groups at the Children’s Cancer Center
- Presentation of research results at international conferences and publication as first author in recognized journals
This position is temporary for three years due to third-party funding and project duration.
Your Profile
- Completed scientific university studies in the field of machine learning, bioinformatics, computer science, data science, applied mathematics, physics, biomedical engineering or another relevant field
- Proven programming experience, especially in Python, good knowledge of ML frameworks such as PyTorch or TensorFlow. Programming experience in R is a plus
- Excellent knowledge of current machine learning methods
- Excellent communication skills and ability to collaborate across disciplines
- Proficiency in written and spoken English; familiarity with German is a plus
- Experience with representation learning, transformer architectures, and explainable AI (XAI) is a plus
- Knowledge of omics data processing and basic molecular biology is a plus but not mandatory, as we care more about your computational skills
- Knowledge of UNIX-based operating systems and version control software is desirable
We look forward to receiving a detailed application including a letter of motivation, CV, references, degree certificates, transcript of records and, if possible, links to code examples, theses or publications.
Immunity status
Please note that employment is contingent upon proof of immunization or immunity against the measles virus, in accordance with applicable legal and medical requirements. Documentation (e.g., vaccination certificate) must be provided before employment begins.
Our Offer
- 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
Contact
Prof. Dr. Michael Bockmayr
m.bockmayr@uke.de
Recruiting Team
- +49 (0) 40 7410-52599
About us
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.
