Job
- Level
- Experienced
- Job Field
- Software, Data
- Employment Type
- Full Time
- Contract Type
- Temporary employment
- Location
- Jülich
- Working Model
- Hybrid, Onsite
Job Summary
In this position, you will develop semantic resources and knowledge engineering approaches for materials science by extracting and structuring scientific knowledge from unstructured sources.
Job Technologies
Your role in the team
- In this position, you will work collaboratively on the following tasks:
- Developing semantic resources and knowledge engineering approaches for materials science, with a focus on structured metadata, semantic interoperability, and knowledge representation.
- Designing methods to extract and integrate scientific knowledge from unstructured and heterogeneous sources, including simulation workflows, publications, and research data repositories.
- Advancing and evaluating the use of LLMs for metadata extraction, schema-guided information extraction, semantic annotation, and ontology-aligned knowledge structuring, including tasks such as entity recognition, relation extraction, attribute/value extraction, and schema population in the materials science domain.
- Developing benchmarks, evaluation datasets, and testing protocols to assess the performance, robustness, and reproducibility of AI and LLM methods for materials science information extraction and metadata generation.
- Contributing to the development and alignment of ontologies, metadata schemas, and related semantic artifacts for materials science and engineering.
- Supporting the integration of semantic and AI technologies into research data management workflows and digital infrastructures, for example within NFDI-MatWerk and related initiatives.
- Disseminating developed tools and concepts through workshops, training activities, and community support in the area of ontology development and semantic data practices.
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Our expectations of you
Education
- University degree (Master, Diploma, or equivalent) in Materials Science or adjacent fields such as Physics, Chemistry, Computer Science, Engineering, or a related discipline. A doctorate is desirable, but not mandatory.
Qualifications
- Expertise in one or more of the following fields is advantageous: materials informatics, ML/AI methods for materials data, simulation workflows, knowledge graphs, ontology development, LLMs, NLP, or information extraction.
- Knowledge of, or willingness to learn, concepts and tools in the field of semantic technologies and knowledge representation, such as Protégé, OWL, SKOS, RDF, or SPARQL.
- Strong communication and teamwork skills, and the ability to work effectively in an interdisciplinary and collaborative research environment
- Willingness to support scientists in research data management and digital knowledge organization.
Experience
- Strong background in computational materials science or computational physics, including scientific programming skills, particularly in Python. Experience in data processing, workflow development, or automated extraction and structuring of scientific information is highly advantageous.
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What we offer
- We work on highly topical, socially relevant issues and offer you the opportunity to actively shape change! You can expect a wide range of opportunities.
- The position offers a varied and diverse role in an international and multidisciplinary environment and the opportunity to work on state-of-the-art methods at the intersection of LLMs, materials informatics, and knowledge engineering.
- Optimal conditions for balancing work and private life, as well as a family-friendly company policy. The option of flexible working (in terms of location) is generally available after consultation and in line with upcoming tasks and (on-site) appointments.
- Flexible working time models, the option of part-time work close to full-time, and 30 vacation days per year.
- Your professional development is important to us - we provide targeted, individual support
- You will receive explicit support with regard to your career development opportunities: https://go.fzj.de/careercenter
- Depending on your existing qualifications and the tasks assigned to you, you will be classified in pay grade 13 of the TVöD-Bund (Collective Agreement for the Public Service). All information on the TVöD-Bund collective agreement can be found on the BMI website. The monthly salaries in euros can be found on page 69 ff. of the PDF download.
- Benefit from attractive additional services such as a company pension scheme with employer contribution. In addition to the basic salary, there is an additional year-end bonus under the collective pay agreement amounting to 75%.
- The position is limited to 3 years with possible long-term prospects
- Our International Advisory Service makes it easier for international employees to get started
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Benefits
Work-Life-Integration
Topics that you deal with on the job
Job Locations
This is your employer
Forschungszentrum Jülich GmbH
Forschungszentrum Jülich is a member of the Helmholtz-Gemeinschaft, making it an effective contributor to solving big challenges our society faces in the realms of information technology, energy, and bioeconomics.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Education System, Science, Research
Research Associate Knowledge Engineering
- Location
- Jülich
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
