registration number:
fb12-0015-wmz-2026
Entry date: as soon as possible
Application deadline: 2026-08-02
Salary: E 13 TV-H
Duration:
2 years
Volume of employment: fulltime
The University of Marburg, founded in 1527, offers a variety of excellent programs of study for around 22,000 students and confronts the important topics of our time through excellent research across a broad spectrum of sciences.
The Department of Mathematics and Computer Science, Artificial Intelligence: Multimodal Modelling and Machine Learning (Ewerth Research Group), is currently accepting applications for a
Research Assistant
The position has a focus on research software engineering and is offered for a period of 2 years. The starting date is as soon as possible. The position is fulltime with salary and benefits commensurate with a public service position in the state Hesse, Germany (TV-H E 13).
The externally funded project “Science-Supporting Recommendation System for Reviewers (WISENT)” focuses on developing a prototype for an open recommendation system for reviewers, designed to meet the real-world requirements of the publication process. It focuses on scientific and technical communities and supports editors of academic journals in identifying reviewers with the relevant expertise for individual submissions. This precise identification of potential reviewers is a major challenge, particularly for publisher-independent publication platforms. The prototype will subsequently be made freely available as a service; the project will also include an implementation for Open Journal System, a widely used journal management software.
Tasks:
- Development of high-performance recommendation algorithms that combine semantic text analysis and bibliometric methods for identifying reviewers
- Implementation and improvement of bibliometric and network analysis methods (citation networks, co-author networks) in accordance with defined requirements
- Evaluation of the algorithms and system components developed using established evaluation metrics
- Design and implementation of a REST API and a web interface to enable editors and editorial teams to use the recommendation system
- Prototype implementation and evaluation of database architectures (PostgreSQL, Neo4j) in close consultation with the SLUB to implement its specifications
- Documentation of the system architecture, API specifications and technical components to support reuse by partners
Within the framework of the third-party funded project, the position offers the opportunity to carry out project-related scientific work. By means of a supervision agreement, it can be ensured that the results obtained may be used for the individual’s own academic qualification outside of working hours. This is a fixed-term project position. The contract is not concluded under Section 2(1) of the German Academic Fixed-Term Contract Act (WissZeitVG).
Profile:
- MSc-degree or equivalent in Computer Science, Information Science or a related subject, with a very good or good grade
- In-depth knowledge of natural language processing and/or machine learning methods for text and data analysis; familiarity with scientific information systems is desirable
- Solid programming skills in Python and SQL; Proven experience with common ML frameworks
- Proven experience in developing web applications using APIs and database-driven systems (SQL) in professional contexts; experience with graph databases (e.g. Neo4j) is an advantage
- Strong communication and teamwork skills, demonstrated through previous collaboration with interdisciplinary research teams or external partners/clients;
- Commitment to open-source development and open scientific infrastructures
We offer:
- Options for remote work
- Flexible working hours
- Ticket for free use of public transport in the state Hesse, Germany
- University sports (sports programmes)
Contact for more Information Dr. Anett Hoppe
+49 6421-28 25621
We support women and strongly encourage them to apply. In areas where women are underrepresented, female applicants will be preferred in case of equal qualifications. As a certified family-friendly university, we support our employees in balancing family and career. A reduction of working time is possible. as discribed in the Social Security Code (Section 2(2) and (3) of Book IX of the Social Security Code (SGB IX)) will be preferred in case of equal qualifications. Application and interview costs can not be refunded.
Please apply by 02.08.2026 using the application button below only.