PhD student or Postdoctoral Researcher (m/f/d)
- University Hospital Würzburg - Clinical Genetics and Genomedicine
- as soon as possible
- Full-time
- Fixed-Term
Application deadline: 30/09/2026
The Institute of Clinical Genetics and Genomic Medicine at the University Hospital Würzburg is seeking a highly motivated PhD student or Postdoctoral Researcher (m/f/d, 75-100% TV-L) with a strong background in bioinformatics to join our team in the field of cancer genomics.
The successful applicant will join an interdisciplinary team working on the German Cancer Aid funded project aimed at dissecting the interactions between leukemic cells, the tumor microenvironment, and the immune system. Within this team, our group will perform single-cell gene expression (GEX) profiling and multimodal data integration of tumor cells derived from the bone marrow of children diagnosed with acute lymphoblastic leukemia.
We offer
- An international, dynamic and multidisciplinary research environment, with opportunities to translate novel scientific findings on patient diagnosis.
- Unlimited access to cutting-edge GPU based servers capable of diverse AI, HPC and computing workloads.
- Flexible working hours and a family-friendly environment, helping you balance personal and professional life.
- Excellent employee benefits, including sports and healthcare workshops, an attractive occupational pension, and a subsidized canteen, to enhance your overall well-being.
Your Tasks
- Establishment of bioinformatic workflows to analyze single cell GEX data, long-read sequencing data, and integration of multimodal data derived using different techniques (i.e., single cell GEX, flow cytometry, long-read sequencing)
- Software development
- Collaboration with wet-lab researchers and clinical partners involved in the project
- Supervision of bachelor and master students
- Publication of results in peer-reviewed journals
- Presentation of research findings at international scientific conferences (e.g., ESHG, ISCB, EHA, ASH)
Project Background
Prognosis and treatment of pediatric acute lymphoblastic leukemia (ALL) are largely determined by underlying genetic alterations. However, in approximately 10% of pediatric ALL no genetic alterations relevant for risk-stratification can be identified using conventional cytogenetic, molecular genetics and short-read sequencing-based methods (B-other). Children diagnosed with B-other ALL receive uniform treatment, despite genetic heterogeneity of their leukemia, resulting in worse outcome (5-year EFS 77.3%) compared to children diagnosed with favorable genetic subtypes. Therefore, discovery of novel biomarkers is urgently required in order to enhance risk stratification, enable tailored therapeutic approaches and improve outcomes in pediatric B-other ALL.
In this project, we will apply long-read whole-genome sequencing, integrated multi-omic and clinical data analysis, and machine learning approaches to characterize the genetic and epigenetic landscape of B-other ALL and identify novel biomarkers for improved risk stratification. Promising candidates will be further investigated in functional in vitro models to assess their biological relevance.
Your Profile
- Master‘s or PhD degree in Bioinformatics, Medical Informatics, Biology, or a related field
- Strong expertise in programming (e.g., Python, R, Perl)
- Basic knowledge of long-read sequencing data generation and single-cell GEX data analysis is a plus
- Excellent written and spoken English
- Independent, structured working style and strong problem-solving skills
- Ability to work in an interdisciplinary team environment
This is what you can look forward to
- Challenging, diverse and evolving area of responsibility
- Attractive salary according to TV-L incl. annual special payment
- Training and Continuing Education
- Retirement Pension Plan
- Company daycare center with extended opening hours
- Company sports program
- Flexible Working Hours
- JobBike
- Corporate Benefits
Become part of the team: Apply now!
Wissenschaftliche Koordinatorin
Tel: +49151 40355882
Remuneration is in accordance with the relevant collective agreements. Severely disabled applicants will be given preference if they are otherwise equally qualified.