Summary
The Johannes Gutenberg-Universität Mainz
(JGU Mainz) is inviting applications for a full-time, 4-year Doctoral Candidate / Research Associate position in the field of Explainable Artificial Intelligence (XAI). The successful candidate will join the XplaiNLP Group
in the Information Systems department within the Faculty of Law and Economics (Fachbereich 03).
Doctoral Candidate (m/f/d) in Explainable Artificial Intelligence (XAI) JGU Mainz, Germany
Designation
Wissenschaftlicher Mitarbeiterin / Doktorand*in (m/w/d) — Research Associate / Doctoral Candidate
Key Information Overview
| Feature | Details |
| Position | Doctoral Candidate (m/f/d) |
| Institution | Johannes Gutenberg-Universität Mainz |
| Research Group | XplaiNLP Group |
| Department / Faculty | Information Systems, Faculty 03 (Law and Economics) |
| Reference Code (Kennziffer) | J158-2026 |
| Pay Grade | EG 13 TV-L |
| Contract Duration | 4 Years (Fixed-term, full-time 100%) |
| Location | Mainz, Germany |
| Application Deadline | August 18, 2026 |
Research Area
- Explainable Artificial Intelligence (XAI)
- Interpretable Machine Learning
- Post-hoc Explainability & Concept-based Explanations
- Causal Inference & Natural Language Processing (NLP)
Location
Mainz, Germany (Campus of Johannes Gutenberg University Mainz)
Eligibility / Qualification
- Degree: An outstanding Master’s degree (or equivalent) preferably in Computer Science or a closely related discipline, ideally with a concentration in Machine Learning, Artificial Intelligence, or Explainable AI (XAI).
- Technical Knowledge: Deep and broad understanding of Machine Learning methods and explainability techniques (e.g., Interpretable ML, Post-hoc Explainability, Concept-based Explanations, Causal Inference).
- Programming Skills: Strong programming expertise in Python and experience with common ML frameworks such as PyTorch or TensorFlow.
- Languages:
- English: Advanced proficiency (at least C1 level required).
- German: Sufficient skills for university-level teaching (at least B1 level desirable).
- Teaching Experience: University-level teaching experience in Machine Learning or Explainable AI is an advantage.
- Soft Skills: High level of initiative, self-reliance, strong communication, organizational, and teamwork abilities, alongside a passion for scientific research and knowledge transfer.
Job Description
- Conduct independent research in the area of Interpretable and Explainable Machine Learning leading to a PhD / doctoral degree.
- Design, implement, and evaluate novel XAI methodologies.
- Publish research findings in top-tier international scientific conferences and academic journals.
- Support university teaching activities (e.g., assisting with lectures, exercises, and seminars in Machine Learning/XAI).
- Assist in the supervision of Bachelor’s and Master’s thesis projects and student advisement.
How to Apply
Applications must be submitted online through the JGU Mainz Job Portal
by clicking the “Jetzt bewerben” button.
Applicants should submit a complete application package containing:
- Cover Letter
- Tabular CV highlighting educational background, internships, research projects, and work experience.
- Academic Certificates (Bachelor’s, Master’s, and other relevant certificates).
- Writing Sample: Master’s thesis and optional relevant research publications (up to a maximum of 40 pages total).
- Portfolio: Link to GitHub profile or portfolio of relevant computational projects (if available).
- Skills List: Bulleted overview of programming skills (languages, frameworks, tools) and specialized knowledge in Machine Learning / XAI.
Last Date for Apply
August 18, 2026
