PhD student (f/d/m) bioinformatics and imaging
MHH Clinic for Pediatric Pneumology, Allergology and Neonatology
The Hannover Medical School (MHH), with about 10.000 employees the biggest company of Lower Saxony, is a university institution for research and teaching in the human and dental medicine and a university hospital of supra-maximum medical care. Research, teaching, medical care and administration work hand in hand in the integration model at the MHH-campus.
You have any questions beforehand?
Prof. Dr. Jonas Christian Schupp
+49 511 532 2699
Apply now online
Reference number 3696
Apply until: 03/01/2026
MHH Clinic for Pediatric Pneumology, Allergology and Neonatology
The Hannover Medical School (MHH), with about 10.000 employees the biggest company of Lower Saxony, is a university institution for research and teaching in the human and dental medicine and a university hospital of supra-maximum medical care. Research, teaching, medical care and administration work hand in hand in the integration model at the MHH-campus.
The German Center for Lung Research and Department of Respiratory Medicine and Infectious Diseases, located at MHH, are looking for a new PhD-Student.
Your PhD project combines cutting-edge computational methods with biomedical data to explore cellular and histological patterns in chronic lung diseases. The aim is to develop and apply advanced algorithms for single-cell genomics and whole-slide image analysis, including unsupervised pattern discovery, spatial mapping, and predictive modeling. The project focuses on uncovering disease-associated cell states and tissue-level patterns directly from large-scale, multicenter datasets, linking these patterns to clinical outcomes such as lung function and survival.
Key computational challenges include:
Your task
Your PhD project combines cutting-edge computational methods with biomedical data to explore cellular and histological patterns in chronic lung diseases. The aim is to develop and apply advanced algorithms for single-cell genomics and whole-slide image analysis, including unsupervised pattern discovery, spatial mapping, and predictive modeling. The project focuses on uncovering disease-associated cell states and tissue-level patterns directly from large-scale, multicenter datasets, linking these patterns to clinical outcomes such as lung function and survival.
Key computational challenges include:
- Designing scalable pipelines for high-dimensional single-cell and imaging data
- Applying machine learning and deep learning techniques to extract meaningful patterns from complex, unannotated data
- Integrating multimodal data (genomics, imaging, clinical) for predictive modeling
- Generating explainable visualizations of discovered patterns and their spatial organization
Your task
- Develop and adapt methods for the analysis of for single-cell genomics and whole-slide image analysis
- Conduct and interpret data analyses
- Prepare regular progress reports
- Contribute to the preparation of scientific publications
- Review and critically assess relevant scientific literature
- Write and defend a doctoral thesis, including presentations of research findings
- University degree in Computational Biology, Computer Science, Bioinformatics, or related scientific field
- Enthusiasm for research questions in pulmonology
- Interest in interdisciplinary work at the interface of medicine and computer science
- Fluent in English, both written and spoken
- Experience with Python, high-performance computing (HPC), and data science methods
- Experience with version management software (e.g. Git) is an advantage
- Ability to work independently, pay attention to detail, and pursue research in a goal-oriented manner
- Ability to constructively handle criticism
- Analytical mindset, strong communication skills, sense of responsibility, teamwork, and reliability
- A part-time position initially limited until 31.January 2029 with 25.03 hours per week at one of the largest employers in the state of Lower Saxony
- Depending on your personal qualifications, remuneration up to pay grade E 13 in accordance with TV-L is possible, with the benefits of public service (e.g. company pension scheme and supplementary insurance through VBL)
- An exciting role at the interface of research, healthcare and science management
- Demanding and multidisciplinary tasks in an innovative and diverse environment
- A lively scientific community across Germany through DZL
- An international and interdisciplinary team
- Possibility of partial remote work
- Personal and professional development opportunities – supported by our wide range of internal and external training and further education programmes
- Excellent public transport connections and the option of leasing a company bicycle
- An outstanding range of sports, counselling and preventive healthcare programmes – because your health is important to us
You have any questions beforehand?
Prof. Dr. Jonas Christian Schupp
+49 511 532 2699
Apply now online
Reference number 3696
Apply until: 03/01/2026
Informationen
Dienststellen:
Einstellungsdatum:
Zum nächstmöglichen Zeitpunkt
Meldeaktenzeichen:
0010
Besoldungs-/Entgeltgruppe:
E 13
Bewerbungsschluss:
01.03.2026
Stellenumfang:
0,65
Plätze:
1
Befristung:
31.01.2029
Stellennummer
114452