Open PhD Position on Knowledge Graphs and Machine Learning for Materials Science

Open PhD Position on Knowledge Graphs and Machine Learning for Materials Science
at FIZ Karlsruhe - Leibniz Institute for Information Infrastructure in the Information Service Engineering research group (FIZ ISE) [3]

We are looking for a suitable person for the open position as PhD in the Information Service Engineering Team. This position is part of the Platform MaterialDigital project ( on the sustainable digitalization of materials. Particular tasks within the project will be the design, implementation, alignment, and maintenance of ontologies for materials science engineering, as well as knowledge extraction from text based sources to populate related knowledge graphs.

We offer:
- Flexible working time models and mobile working/home office – you are required to spend only 20 % of your monthly working time in the office (although we have very good coffee at FIZ Karlsruhe and are happy about exchange within the team, so attendance is always welcome).
- We are happy to share our coffee enthusiasm [1] as well as looking forward to getting to know new hobbies and activities in addition to our already established running group.
- With us, you will get the chance to work in a diverse team [2] with colleagues that are more than happy to welcome new team members of all backgrounds, genders and ages.
- Because our team is not only based at FIZ Karlsruhe [3], but also at KIT [4], we offer you the opportunity to gain experience in teaching and to engage in discourse with students at KIT, either in person or through our online formats [5].
- In addition, we offer a productive and a constantly developing research and working environment and actively support you in your further scientific endeavors.
- The salary is based on the collective labour agreement for the public service in Germany (TVöD VKA) and in addition you will receive the company pension plan with the VBL.
- Furthermore, we are certified by the audit berufundfamilie [6], which guarantees the compatibility of family and career.
- If you wish to combine work, sport, and sustainability, our institute offers company bike leasing [7] options.

We are looking for a person with:
- A very good master's degree in computer science or a comparable discipline – however, people who do not have this qualification but can impress with their research work are explicitly encouraged to apply.
- Excellent written and spoken English, German language skills are an advantage.
- Motivation and excitement in dealing with challenging research problems and in developing convincing solutions together.

In addition, we look forward to unique contributions to enhance our team with:
- Publications of research results in renowned peer-reviewed journals and conferences.
- Excellent software engineering skills and the ability to develop mature software components beyond pure research prototypes.
- Knowledge of materials science is a plus, but not required.

Optimally, you have expertise in one or more of the following research areas:
- Knowledge Graphs and Semantic Web Technologies
- Machine Learning and Deep Learning
- Ontology Design and Ontological Engineering
- Natural Language Processing

More information about us:
Information Service Engineering (ISE) [8] at FIZ Karlsruhe, led by Prof. Dr. Harald Sack [9] who is also heading the KIT research group of the same name [10], investigates models and methods for efficient semantic indexing, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination with symbolic logic are applied. ISE research relies and extends on knowledge representation standards developed for the Semantic Web. ISE research application areas include but are not limited to solutions for knowledge extraction, semantic annotation, semantic and exploratory search, as well as recommender systems and question answering. Besides basic methodological research, domains of applied ISE research are, amongst others, cultural heritage, digital humanities, materials science, and research data management.

FIZ Karlsruhe – Leibniz Institute for Information Infrastructure is one of the leading providers of scientific information and services and a member of the Leibniz Association. Our core tasks are the professional provision of research and patent information to science and industry as well as the development of innovative information infrastructures, e.g., with a focus on research data management, knowledge graphs and digital platforms. To this end, we conduct our own research, cooperate with renowned universities and research societies, and are internationally and interdisciplinarily networked. FIZ Karlsruhe is a limited liability company with a non-profit character and one of the largest non-university institutions of its kind.
We welcome applications from driven individuals seeking a successful scientific career in the context of knowledge graphs.

Your tasks in the ISE research team are:
- Innovative research on FIZ ISE research topics with participation in scientific publications, third-party funding proposals, and academic activities.
- The supervision of master and bachelor theses.
- The employment is initially limited to two years, although our goal is a long-term cooperation. Applications from severely handicapped persons will be considered with preference, provided they are equally qualified. Information on data protection for employment advertisements can be found here.

If you have any technical questions, please contact Prof. Dr. Harald Sack (

Excellent candidates are invited to apply with:
1) detailed curriculum vitae
2) copies of degree certificates & transcripts
3) publication record (or writing samples from your thesis)
4) letters of recommendation (preferably at least two)
5) a letter of motivation covering your research goals

Please send your complete application documents by email, quoting the reference number 43/2022, to











Received on Thursday, 22 December 2022 15:42:50 UTC