Bitte beachten Sie: Diese Stellenanzeige ist nicht mehr aktiv.
Entdecken Sie hier weitere Stellenanzeigen auf academics, dem führenden Stellenmarkt für Wissenschaft und Forschung. Um regelmäßig per E-Mail über passende Stellen informiert zu werden, können Sie sich jederzeit kostenlos registrieren.
Research Assistant (f/m/d) for research-based software engineering in the area of text mining with machine learning methods
Leibniz-Informationszentrum Wirtschaft (ZBW)
At our unit "Academic Services", we are looking for a
RESEARCH ASSISTANT [F/M/DIV]
for research-based software engineering in the area of
text mining with machine learning methods
The position is located in Kiel or Hamburg (depending on the applicant‘s
preferences), Germany, and will start as soon as possible. This is
a full-time position (currently 38.7 hours per week), part-time work is
possible to a certain extent. We offer a contract that is initially fixed to
a period of 4 years in accordance with § 2 Wissenschaftszeitvertragsgesetz
(WissZeitVG), with remuneration based on the public sector pay
scale at grade EG 13 TV-L.
to conceptualize, develop and apply machine learning methods in
the area of text mining with a focus on semantic metadata extraction
to implement and adapt software solutions for the enrichment of
information resources in the domain of economics with semantic
metadata extracted from texts, preferably in Python
to integrate those software solutions into the productive workflows
for semantic annotation of resources at ZBW
to document and version your own software solutions in order to
ensure their reusability (within the limits of available software
licenses), preferably in Git-based environments
to support ZBW in networking with other institutions on the international
and the national level in the area of automated metadata
extraction / of machine learning, e.g. via publishing articles and
giving talks at corresponding scientific conferences
…essential qualifications / skills:
Master or diploma in computer science, business informatics, computational
linguistics, information science, or in a related technical
established methodological knowledge and practical experience in
the implementation of methods of natural language processing and
machine learning – preferably also of neural networks / deep learning
– for the area of text mining / information retrieval
experience in implementing using a higher programming language
and corresponding developing environments and libraries, as well as
source code management
good command of written and spoken English
strong communication skills, intercultural competence, and the
ability to cooperate in an interdisciplinary context
with the administration of backend systems
with the development of frontend applications, e.g. web applications
or visual user interfaces
with the implementation of state of the art software architectures,
e.g. microservice architectures
with library-specific applications, data formats, and information
Good command of written and spoken German is a plus.
We expect you to be able to go on business trips and day trips to the
respective other location of ZBW.
a challenging task in a dynamic environment where team work,
transparency, innovation, and continuous learning are essential
the possibility of obtaining a PhD degree in computer science
the public sector pension plan (VBL)
a work place on the Firth of Kiel or in the centre of Hamburg.
The ZBW – Leibniz Information Centre
for Economicsis the world‘s largest information
centre for economic literature. The
institution holds more than 4 million volumes
and enables access to millions of online documents
in economics. ZBW is a research-based
academic library and a member of the Leibniz
Association. In addition, ZBW is scientifically
affiliated to the Kiel University and conducts
its own application-oriented research in computer
science and information science, with a
focus on Open Science.
With its expertise both in economics and
in information science, the unit "Collection
Development & Metadata" provides an
essential base for the products and services
offered to the patrons of ZBW. The unit
handles the creation, curation, and standardization
of metadata, resource management
and information services, thus enabling
and promoting better access to relevant
information in economics and information
processing services that are tailored specifically
to the needs of the patrons of ZBW.
In order to optimize the supply of information
continuously and in accordance with
the demands of our patrons, the resources
provided via ZBW are processed with respect
to their contents and annotated with
structured and standardized metadata so
that those resources can be reliably found
in the context of domain-specific retrieval
and aggregation processes. These metadata
can then be used for further information
processing applications as well.
Due to the proliferation of digital publications,
it has become impossible to create
comprehensive metadata for all publications
intellectually. Therefore, at ZBW we
reuse and adapt research results on Artificial
Intelligence with respect to our specific
context: We extract semantic features from
resources using machine learning methods
in order to obtain high-quality metadata
(semi-)automatically and thus to be able to
improve the relevance of search results in
our portal EconBiz even further.
Are you interested in joining the team?
online now (ID-Nr. A1-04).
For further information please contact
Dr. Anna Kasprzik (firstname.lastname@example.org,
The foundation aims to increase the proportion
of women in its staff and encourages
suitably qualified women to apply. Female
candidates will be given priority in the case
of equal suitability, competence and professional
The ZBW has an equal opportunities policy
for persons with recognized disabilities.
Disabled persons with the necessary qualifications
will therefore be given priority.
Please submit your application with the relevant
documents online by February 8th,
2019. Please do not submit a photo with
We look forward to meeting you!
Um unsere Webseite optimal gestalten und fortlaufend verbessern zu können, verwenden wir Cookies. Durch die weitere Nutzung der Webseite stimmen Sie der Verwendung von Cookies zu. Weitere Informationen sowie Hinweise dazu, wie Sie die Speicherung der Cookies verhindern können, finden Sie in unserer Datenschutzerklärung.