Research Associate (m/f/d) in the field of computer science

Bremen Research; Bremen; Hybrid; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A research institute in Bremen seeks a Research Associate in computer science. The role involves developing information systems for research projects and offers a family-friendly environment with flexible working options. Requirements include a master's degree, strong Python skills, and knowledge in data mining and NLP. Applications close on 02.10.2025.

Leistungen

Annual bonus

Company pension scheme

Support for personal further qualification

Flexible working time models

Corporate health management

Qualifikationen

• Completed master's or diploma degree in computer science.
• Very good knowledge of Python and ability to contribute to existing development.
• Prior knowledge of data mining, natural language processing, or LLM training.
• First experience with semantic web technologies (OWL/SPARQL) and ontologies.
• First experience in conducting research projects with scientific partners and industry.

Aufgaben

• Working on the research project ‘Platform Material-Digital’.
• Development of a distributed information system for semantic process chain modelling.
• Conducting an assessment of the current situation with scientific and industrial partners.
• Conceptual and modular development of a data transformation pipeline.
• Participation in national and international seminars and conferences.

Kenntnisse

Python

Data mining

Natural language processing

Semantic web technologies

Conducting research projects

Ausbildung

Master's or diploma degree in computer science

Jobbeschreibung

Join our team as a Research Associate (m/f/d) in the field of computer science on a full-time basis (39.2 hours per week), limited to three years.

What you can expect from us:

• remuneration based on the federal collective bargaining agreement (TV-L), pay group 13 (from EUR 4,630 per month full-time), annual bonus, company pension scheme
• support for personal further qualification as part of a doctorate (Dr.-Ing.) in cooperation with the University of Bremen
• family-friendly, flexible working time models, part-time option, remote work, additional days off on December 24 and 31
• corporate health management and sports activities through egym wellpass
• interdisciplinary and international environment

We need your expertise for:

• working on the research project ‘Platform Material-Digital’
• development of a distributed information system for semantic process chain modelling that can describe changes in material properties
• conducting an assessment of the current situation with other scientific and industrial partners in Germany for the purpose of sharing data in accordance with guidelines
• conceptual and modular development of a (partially) automated data transformation pipeline from raw data to statement graphs
• participation in national and international seminars and conferences, as well as exchange with other research partners in topic-related working groups

What we expect from you:

• completed master's or diploma degree in computer science
• very good knowledge of Python and the ability to familiarise yourself with and contribute to existing development activities
• prior knowledge of data mining, natural language processing, or LLM training
• first experience with semantic web technologies (OWL/SPARQL) and ontologies
• first experience in conducting research projects with scientific partners and industry

Leibniz-IWT is a certified family-friendly research institute and actively pursues equality for all groups of people. We promote the professional development of women at the institute and strongly encourage them to apply. You can find information on our representative body for severely disabled persons and inclusion officer on our homepage. Applicants with severe disabilities will be given preferential consideration if they are equally qualified.

Please send your application including a cover letter, CV and graduation certificates until 02.10.2025, quoting the reference number V 25-2.