FULL TIME | INITIALLY LIMITED TO 3 YEARS | ANNOUNCEMENT NUMBER: 222-2025

We are currently seeking a motivated PhD Student to work on a collaborative project between the Research Group of Computational Immunology, led by Prof. Dr. Katharina Imkeller, and the Research Group of Machine Learning in Oncology, led by Prof. Dr. Florian Buettner.
The Buettner lab (https://mlo-lab.github.io) works on the intersection of machine learning and oncology and as such is actively pursuing original research in both areas. The Imkeller lab (https://agimkeller.github.io) applies mathematical and computational methods to understand the inter- and intra-individual heterogeneity of tumor-immune interactions in humans. Both labs feature regular publications in high-impact journals. Together, we will develop statistically sound algorithms and user-friendly tools to integrate complex molecular data for comprehensively characterizing tumor microenvironments via single-cell transcriptomics, spatially-resolved proteomics and transcriptomics. The PhD position is embedded within the LOEWE program “CARISMa” (Optimierung von CAR-Zelltherapien durch Beeinflussung des ImmunSuppressiven Tumor-Mikromilieus), which aims to optimize cellular therapies by modulating the immunosupressive microenvironment of solid tumors.
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Your role

• The planned PhD project focuses on the development and collaboration-driven application of computational methods to integrate different types of omics data and making them available for clinical use. Relevant data types include single cell transcriptomics, spatially-resolved multi-omics such as multiplexed immunofluoresence images and spatial transcriptomics.
• The PhD student will develop novel approaches for spatial data integration, perform analysis of multi-omics datasets generated within the CARISMa program and communicate the results with clinical collaboration partners.

Who you are

• You have a master’s degree in bioinformatics, statistics, biophysics or related field (or a degree in biology/medicine with excellent mathematics and programming skills).
• You have hands-on experience in software development and data analysis (Python or R).
• You have a good knowledge of machine learning and statistics.
• You have a strong interest in immunology or cancer biology.
• Ability to conduct independent research and motivation to join an international and interdisciplinary research team.
• Fluency in English language.
• Due to legal regulations, valid proof of measles immunity / measles vaccination is required.

What we offer

• Working environment: Interesting collaborative research projects in immunooncology and immunotherapy. State of the art research infrastructure, an inspiring working environment and excellent basic research with translational and clinical applications. Dedicated personal mentoring and participation in training and qualification programs of the MSNZ and the Goethe University.
• Collective agreement: In addition to an attractive salary based on a collective agreement (TVGU E13 (65%)) with an annual special payment, you benefit from long-term security through company pension schemes.
• Mobility: Free public transport in all Hessen (Free State Ticket Hessen)
• Campus: Our attractive university hospital campus offers a modern cafeteria, various cafes, and opportunities to rest in numerous green spaces. A walk on the riverside of the Main offers relaxation during breaks
• Work-Life-Balance: Part-time employment is possible, we offer childcare in our daycare center (if you have any questions, please contact UKF-Familienservice), child care during holidays
• Health Promotion: Benefit from our attractive health offers. We offer regular online and face-to-face courses on nutrition, relaxation, sports and exercise.
• Professional development: Internal and external training for your professional development
• Any questions? Many answers can be found in our FAQs for new employees. If you have any further questions, please do not hesitate to contact us.

Disabled applicants are preferred if they have the same personal and professional qualifications.

• The planned PhD project focuses on the development and collaboration-driven application of computational methods to integrate different types of omics data and making them available for clinical use. Relevant data types include single cell transcriptomics, spatially-resolved multi-omics such as multiplexed immunofluoresence images and spatial transcriptomics.
• The PhD student will develop novel approaches for spatial data integration, perform analysis of multi-omics datasets generated within the CARISMa program and communicate the results with clinical collaboration partners