Doctoral Researcher (Ph.D. candidate) (m/f/d) Computational Immunology

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

Desirable qualifications:

• Prior experience in working with biological high-throughput molecular data (e.g., bulk or single-cell RNA-seq)
• Familiarity with software development tools (e.g., Git, reproducible workflows)
• Basic knowledge of RNA biology and immunology

We support women and strongly encourage them to apply. As a certified family-friendly university, we support our employees in balancing family and career.

Applicants with a disability as described in SGB IX (§ 2 Abs. 2, 3) will be preferred in case of equal qualifications.

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