Postdoctoral Researcher (m/f/d) Computational Immunology
Faculty of Informatics and Data Science
Entry date: as soon as possible
Volume of Employment: 40h / week
Salary: TV-L E13
Duration: for 4 years
Application deadline: 2026-11-11
Job-ID: 26.229
We offer:
- An internationally leading, well-funded research environment at the intersection of data science, RNA biology, and immunology
- Access to unique primary datasets through close collaborations with renowned international experimental labs, offering strong potential for high-impact publications
- The opportunity to contribute to and shape our widely used open-source software ecosystem (GRAND-SLAM and PRICE)
- Active support for your academic career development, including opportunities for independent research, grant writing, teaching, and student co-supervision
- State-of-the-art high-performance computing infrastructure and an international, interdisciplinary team
- Flexible working arrangements (including flexible hours and partial remote work) to support diverse life situations
Your tasks:
- Conceptualization, mathematical derivation, and implementation of novel statistical and computational methods
- Leading data-analytical projects in close collaboration with our network of experimental research partners in immunology and virology
- Writing high-impact scientific publications and presenting research findings at leading international conferences
- Active contribution to teaching activities (lectures, seminars, and practical courses, taught in English) within the study programs of the Faculty of Informatics and Data Science
- Co-supervision and mentoring of PhD, Master, and Bachelor students in the group
- Assistance in drafting grant proposals and maintaining open-source scientific software packages
Your profile:
- An excellent doctorate (PhD) in bioinformatics or computational biology is required
- Solid practical and theoretical expertise in statistical modeling, high-dimensional data analysis, and machine learning is required
- Advanced programming proficiency (preferably in R, Python, or Java) and familiarity with software engineering best practices (e.g., Git, package development) are essential
- A proven track record of scientific publications in international peer-reviewed journals and excellent English communication skills are required
- Active commitment to academic teaching and student mentoring is expected; prior supervisory experience is a plus
- Hands-on experience with the analysis of sequencing data (e.g., transcriptomics, single-cell genomics) is advantageous
Further Information
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, PRICE) with cutting-edge applications in RNA biology, 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.
The temporary employment is for scientific qualification with a contract duration of 4 years (§ 2 para. 1 WissZeitVG). The position is suitable for part-time work.
How to apply
We look forward to receiving your application through our online application portal only, using the button below.
Contact for more information
Prof. Dr. Florian Erhard
+49 941 943-68608
[email protected]
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 described 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.
Universität Regensburg
Universitätsstraße 31
93053 Regensburg