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Independent Research Group Leaders (f/m/d) for Computational RNA Biology
Independent Research Group Leader (f/m/d) for Computational RNA Biology
The Frankfurt Institute for Advanced Studies (FIAS) and the newly funded Cluster of Excellence SCALE (SubCellular Architecture of LifE) are seeking an Independent Research Group Leader (f/m/d) in Computational RNA Biology.
Our Mission
The primary goal of SCALE and FIAS is to create Digital Twins of sub-cellular architecture, mapping and simulating the internal structure of cells with unprecedented detail. By integrating RNA and spatial ribonomics data, we aim to deepen our understanding of key biological processes and their relevance to major diseases, including bacterial resistance, neurodegeneration, and inflammation.
We Offer
- A competitive group leader salary and a 5-year appointment
- Funding for two PhD students and running costs
- Co-affiliation with Goethe University Frankfurt (upon consideration)
- A research environment at FIAS, integrated into the SCALE Cluster and the Research Campus Riedberg, which provides advanced infrastructure for computational biology
Your Profile
We seek an outstanding early-career scientist to establish an independent research program in Computational RNA Biology. The successful candidate will develop theoretical, computational, and AI-based approaches to investigate how RNAs and RNA-binding proteins control:
- Gene regulation
- Protein function
- Subcellular organization
- Biomolecular condensation
- Intracellular transport
A collaborative and open-science attitude is essential.
Research Focus Areas
Candidates should establish an innovative and internationally competitive research program in at least one of the following areas:
1. Modeling RNA in Biological Systems
- Development of mathematical, multiscale, and agent-based models to understand how RNAs and ribonucleoprotein (RNP) assemblies regulate:
- Gene expression
- Cellular behavior
- Subcellular organization
- Integration of transcriptomics, ribonomics, interactomics, structural biology, and imaging datasets into predictive computational frameworks
- Application of:
- Atomistic simulations
- Coarse-grained modeling
- RNA folding prediction
- RNA-protein and RNA-small molecule interaction modeling
- Polymer physics
- Statistical inference
to study RNA structure, function, transport, and regulatory mechanisms in health and disease
2. AI and Machine Learning for RNA Biology
- Development of:
- Deep learning
- Graph neural networks
- Generative AI
- RNA foundation models
to analyze large-scale omics, spatial transcriptomics, ribonomics, and imaging datasets
- Use of AI to predict:
- RNA structure and localization
- Regulatory functions
- RNA-protein interactions
- Condensate formation
- Effects of mutations and disease-associated perturbations on RNA-dependent regulation and cellular organization
3. Integrative Structural and Spatial RNA Biology
- Integration of multimodal datasets, including:
- Cryo-EM and Cryo-ET
- Super-resolution microscopy
- Single-molecule imaging
- Spatial omics
- CLIP-based interaction maps
- Large-scale imaging datasets
for comprehensive modeling of RNA-containing molecular assemblies and subcellular architecture
- Development of scalable visualization, analysis, and software solutions for RNA-centered cell biology
Diversity & Inclusion
FIAS and SCALE are committed to fostering a workplace culture that promotes equality, diversity, and inclusion. We strongly encourage applications from qualified individuals regardless of gender, nationality, ethnic or social origin, religion, disability, age, or sexual orientation. Severely disabled persons with equal qualifications will be given priority.
Your Application
Submit your application by 30 August 2026 via our online portal:
https://jobapplication.hrworks.de/de?companyId=amb4af72&id=301ce0
Required documents:
- CV
- Research statement (past achievements and future plans, max. 4 pages)
- List of annotated top 5 publications
Potential candidates will be invited to a symposium for a presentation and interview.
Contact
For further questions, please reach out to:
- Scientific issues: Prof. Michaela Müller-McNicoll (mueller-mcnicoll@bio.uni-frankfurt.de)
- Administrative issues: Meike Taplik (hr@fias.uni-frankfurt.de)
Frankfurt Institute for Advanced Studies (FIAS)
Ruth-Moufang-Str. 1
60438 Frankfurt am Main