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

Universität Regensburg; Regensburg; Hybrid; EUR 56.000 - 72.000; Vollzeit

Benefits dieser Stelle

DFG-funded project

Open-source tools (GRAND-SLAM/grandR)

Mentoring & training

Conference travel support

Flexible hours

Partial remote work

Zusammenfassung

Universität Regensburg invites applications for a Doctoral Researcher (Ph.D. candidate) in Computational Immunology within the Faculty of Informatics and Data Science. The role offers a funded, 3-year path with a flexible schedule and partial remote work.

You will develop statistical methods for single-cell RNA sequencing data, contribute to GRAND-SLAM/grandR, and be mentored through an international research group. A Master’s degree in a quantitative field is required.

Qualifikationen

• Master’s degree or equivalent in a quantitative field (bioinformatics, statistics, computer science, data science, physics) is required.
• Solid theoretical knowledge of statistical methods and practical programming experience (R, Python, or Java) is required.
• Good English communication skills and motivation for interdisciplinary research bridging data science and biology are expected.
• Prior experience with biological high-throughput molecular data (bulk or single-cell RNA-seq) is desirable.

Aufgaben

• Develop and implement statistical methods and algorithms for single-cell RNA sequencing data, focusing on metabolic RNA labeling (scSLAM-seq).
• Apply computational tools to data from collaboration partners.
• Maintain and extend software packages (GRAND-SLAM/grandR).
• Publish results in peer-reviewed journals and present at international conferences.
• Pursue a doctoral degree with structured supervision.

Kenntnisse

Statistics

Programming (R/Python/Java)

English communication

Bioinformatics knowledge

Ausbildung

Master’s degree or equivalent

Tools

Git

Reproducible workflows

Jobbeschreibung

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

Computational Immunology

Faculty of Informatics and Data Science

Details

• Entry date: as soon as possible
• Volume of employ-ment: full-time40 h / week (part‑time suitable)
• Salary: TV-L E13
• Duration: limited to 3 years*

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: [e-mail], phone: [phone]

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"