• Development of computational methods and processing pipelines dedicated to the project
• Application of existing and development of new analytical and ML solutions
• Data visualization and communication
• Work in close collaboration with our medical collaboration partners
• Managing the project in terms of data organization and analysis

• M.Sc. degree in computer science, physics, bioinformatics, or a related field
• Excellence in programming (Python)
• Proven experience with deep learning
• Experience with computation on cluster architectures is a plus
• Great communication and organizational skills, capacity of working in a team and in an interdisciplinary environment

• Opportunity to apply and develop cutting-edge machine learning and computational technologies to resolve timely medical and scientific problems
• Collaborative, and international multi-disciplinary working environment where colloquial and working language is English
• Development and networking through participation in workshop and conferences both ML and biology or medicine

Research overview:
We are looking for a PhD candidate to join our project within the Collaborative Research Center 1530 “Elucidation and targeting of pathogenic mechanisms in B cell malignancies”.
As a part of this interdisciplinary research consortium, we will analyze histopathology image data to improve diagnosis, risk stratification and outcome prediction in patients with chronic lymphocytic leukemia. A major focus of the project is the identification of morphological and spatial tissue features associated with Richter transformation, i.e. the progression of CLL into aggressive lymphoma.
The project combines state-of-the-art machine learning, image analysis and cancer biology. In later stages of the project, image-derived information will be integrated with other data modalities, such as transcriptomic and genomic data.
The PhD project is jointly supervised by two principal investigators with complementary expertise in computational image analysis and hematology.
Research Environment:
Bozek Lab: Located at the biomedical campus of the University of Cologne the “Data Science of Bioimages lab” is working on data-intensive problems in biomedicine by combining machine learning, statistical and other computational methods. Image data and deep learning solutions represent key focus of our research. Embedded in the thriving biomedical research hub of Cologne, we are involved in scientific collaborations with partners across medical disciplines and address questions ranging from histopathology of cancer to behavioral changes in neurodegenerative diseases. Please visit https://www.bozeklab.com/ to learn more about the group’s interests and ongoing research.
Al-Sawaf Lab: Also located at the biomedical campus of the University of Cologne, at the CECAD research center, the “Integrated Cancer Research Laboratory” focuses on translational research in hematological malignancies, particularly chronic lymphocytic leukemia, lymphoma and secondary solid cancers. The group combines clinical, molecular and computational approaches to study disease progression, treatment response and mechanisms of transformation. Please visit https://www.al-sawaf-lab.com/ to learn more about the group’s research activities.