PhD/Junior Researcher or PostDoc/Senior Researcher (f/m/x)

19/2024

FIZ Karlsruhe – Leibniz Institute for Information Infrastructure is one of the leading provider 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. For this purpose, we conduct in-house research, cooperate with renowned universities and research associations and maintain an international network. FIZ Karlsruhe is a GmbH (a limited liability company) with a non-profit character and one of the largest non-university institutions of its kind in Germany.

Information Service Engineering (ISE) at FIZ Karlsruhe, led by Prof. Dr. Harald Sack, 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 knowledge representation are applied (Hybrid AI). 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.

We are recruiting for the open position as a PhD/Junior Researcher or PostDoc/Senior Researcher (f/m/x) for our location in Karlsruhe as of 1 January 2025. We are looking for an ambitious person who aims to have a successful scientific career in the context of knowledge graph and machine learning related technologies contributing to the strategic research and technology goals of FIZ Karlsruhe. For this position in particular, the candidate will work in the project “Themenportal Wiedergutmachung” funded by the German Federal Ministry of Finance (BMF).

Job Description:

Conducting innovative research on research topics related to the project, e.g., knowledge
graphs, deep learning and large language models, ontological engineering, and natural
language processing with participation in scientific publications and other academic activities.
The co-supervision of master and bachelor theses (additionally, co-supervision of PhD students
for PostDocs).
Project-management related activities, e.g. internal and external coordination, reporting,
acquisition of third-party funding, etc.

Qualifications and Skills:

A very good master's degree (for PostDocs: PhD degree) in computer science or a comparable discipline.
Very good software engineering skills and the ability to develop mature software components beyond pure research prototypes.
Very good written and spoken English, German language skills are an advantage but are not mandatory.
Motivation and excitement in dealing with challenging research problems and in developing convincing solutions as a team.
For PostDocs/Senior Researchers:
– Publications of research results in renowned, peer-reviewed journals and conferences.
– Experience in the acquisition of funding from national, European and/or international funding agencies is highly beneficial, but not mandatory.

Optimally, you have expertise in one or more of the following research areas:

Machine Learning, Deep Learning and Large Language Models
Knowledge Graphs and Semantic Web Technologies
Natural Language Processing
Ontology Design and Ontological Engineering

The candidate should be highly self-motivated, interested in tackling challenging research problems, have very good organizational skills, be open minded, and have scientific leadership potential.

Why FIZ Karlsruhe:

Promoting the scientific development of young researchers is an important goal of FIZ Karlsruhe. PhD candidates will be supervised by Prof. Dr. Harald Sack (FIZ Karlsruhe & KIT).
With us, you will get the chance to work in a diverse team 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, but also at KIT, 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.
In addition, we offer a productive and a constantly developing research and working environment and actively support you in your further scientific endeavors.
Flexible working time models and mobile working up to 80 per cent
Remuneration according to the German Collective Agreement for the Public Sector (TVöD VKA) including a company pension plan with VBL
A family friendly work environment certified by audit berufundfamilie
Company bike leasing option and €25 employer subsidy for the Deutschland-Ticket

The employment relationship is initially limited to two years, although our goal is a long-term cooperation. The position is full-time with the option of part-time employment.

Applications from severely handicapped persons will be considered with preference, provided they are equally qualified. Information on data protection for job advertisements can be found here.

If you have any technical questions, please contact harald.sack [at] fiz-karlsruhe.de (Prof. Dr. Harald Sack). Questions regarding the application process should be directed to bewerbung [at] fiz-karlsruhe.de (bewerbung[at]fiz-karlsruhe[dot]de).

Please send your complete application documents by e-mail, quoting the reference number 19/2024, to bewerbung [at] fiz-karlsruhe.de (bewerbung[at]fiz-karlsruhe[dot]de). Application period until 30 September 2024.

detailed curriculum vitae
copies of degree certificates & transcripts
publication record or writing samples from your thesis
letters of recommendation (preferably at least two)
a letter of motivation covering your research goals