Doctoral Researcher (Ph.D. candidate) (m/f/d) Computational Immunology Universität Regensburg
Doctoral Researcher (Ph.D. candidate) (m/f/d)
Computational Immunology
Our research group is internationally leading in developing computational and statistical methods for metabolic RNA labeling data, with a strong focus on single-cell technologies (scSLAM-seq). We combine rigorous statistical modeling and high-performance software development (e.g., GRAND-SLAM, grandR) with cutting-edge applications in RNA kinetics, virology, and immunology. Our interdisciplinary team works at the interface of data science and high-throughput molecular biology, maintaining close collaborations with experimental labs worldwide to decode the temporal dynamics of gene regulation.
We offer:
- A dedicated DFG-funded research project focused on novel method development with a strong potential for high-ranking publications
- Close integration into an internationally leading research group specializing in computational methods for metabolic RNA labeling and single-cell genomics
- Direct contribution of your methodological work to established open-source tools (GRAND-SLAM/grandR) used by researchers worldwide
- Structured, close mentoring and comprehensive training in theoretical and practical bioinformatics, statistical modeling, and interdisciplinary communication
- Full financial support for presenting your research at national and international conferences
- Flexible working arrangements (including flexible hours and partial remote work) to support diverse life situations
Your tasks:
- Development and implementation of statistical methods and algorithms for single-cell RNA sequencing data, with a special focus on metabolic RNA labeling (scSLAM-seq)
- Application of developed computational tools to data generated by our network of collaboration partners
- Contributing to the maintenance and extension of our software packages (e.g., GRAND-SLAM / grandR)
- Publication of research results in peer-reviewed scientific journals and presentations at international conferences
- Pursuit of a doctoral degree (Dr. rer. nat. / PhD) supported by structured supervision
Your profile:
- A university degree (Master’s or equivalent) in bioinformatics, statistics, computer science, data science, physics, or a related quantitative field is required
- Solid theoretical knowledge of statistical methods and practical programming experience (preferably in R, Python, or Java) are required
- Good communication skills in English, a high degree of intrinsic motivation, and the willingness to conduct interdisciplinary research bridging data science and biology are expected
- Prior experience in working with biological high-throughput molecular data (e.g., bulk or single-cell RNA-seq) is desired
- Familiarity with software development tools (e.g., Git, reproducible workflows) and basic knowledge of RNA biology and immunology is beneficial
We support women and strongly encourage them to apply. As a certified family-friendly university, we support our employees in balancing family and career (more information: https://www.uni-regensburg.de/universitaet/jobs-und-karriere/familien-service). Applicants with a disability as discribed in SGB IX (§ 2 Abs. 2, 3) will be preferred in case of equal qualifications. Please indicate any severe disability in your application, if applicable. Application and interview costs can not be refunded.
Contact for more information:
Contact person: Dr. Florian Erhard, mail: Florian.Erhard@ur.de, phone: +49 941 943-68608
Please apply by 2026-10-03 using the application-button below.
***** "This position is available for a fixed term of three years within the framework of the project "Unraveling crosstalk of virus infection and cytokine signaling by heterogeneity sequencing 2.0"
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Universität Regensburg
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