PhD Candidate Information Retrieval, Information Extraction

16 May 2023
Job Information

Organisation/Company

GESIS - Leibniz-Institut für Sozialwissenschaften

Department

Cologne/Mannheim

Research Field

Sociology

Researcher Profile

First Stage Researcher (R1)

Country

Germany

Application Deadline

6 Jun 2023 - 23:59 (Europe/Berlin)

Type of Contract

Temporary

Job Status

Part-time

Hours Per Week

31,36

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Reference Number

KTS-50

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

GESIS – Leibniz-Institute for the Social Sciences is an internationally active research institute, funded by federal and state governments and member of the Leibniz Association.

For the next possible date our Department Knowledge Technologies for the Social Sciences (KTS), Team FAIR Data located in Cologne, is looking for a

PhD Candidate Information Retrieval, Information Extraction

(Salary group 13 TV-L, working time 80%, limited to September 2026)

The department Knowledge Technologies for Social Sciences (KTS)  conducts research at the intersection of information retrieval, knowledge graphs, human information interaction and machine learning as foundation for innovative web portals and platforms for the search and use of research data. KTS innovations are based on a state-of-the-art software stack and research-based innovations in the aforementioned fields.

In the context of the consortium BERD@NFDI of the National Research Data Infrastructure (NFDI ), KTS develops innovative services with the goal to improve the search for and the findability of research data.

Your tasks will be:

• Research in the areas of data search, web data discovery, information retrieval and/or information extraction, with respect to research data
• Conceptual design, modeling and implementation of research-based services for harvesting and extraction of as well as search for research data
• Implementing and monitoring strategies to improve data visibility and findability on the web
• Engagement with partners in the consortium and the NFDI
• Dissemination of project results through publications and workshops

Your profile:

• Good university degree (Master/diploma or equivalent) in Computer Science, Data Science or comparable fields
• Knowledge in the areas of data and information retrieval, information extraction (NLP/ML) and/or knowledge graphs
• Experience in software development with Java, Elasticsearch, Web and DB technologies
• Good oral and written communication skills in English, knowledge of German desirable

Our Benefits:

• A fast growing and international working environment with a lot of creative scientific freedom and access to unique research data
• Excellent career opportunities in research & teaching as well as in software development and data engineering
• Close collaboration and exchange with excellent national and international research labs in AI and data science
• Flexible working hours and the possibility of up to 60% mobile working within Germany
• Very good conditions for reconciling work and family life, e.g. subsidies for childcare for children who have not yet attained the age of compulsory schooling
• Holistic company health management and discounted participation in the university's sports programme
• Generous support for your pension provision as a direct insurance policy
• Promotion of your skills through further training measures

For further information concerning the tasks, please contact Peter Mutschke via phone +49 (0221) 47694 - 500 or via E-Mail . If you have questions about the application process, please contact Franca Tosetti via E-Mail.

Interested?

Please apply via our Online-application portal until June, 06th  2023.

Our reference number is: KTS-50.

Requirements

Research Field

Sociology

Education Level

Master Degree or equivalent

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

GESIS - Leibniz-Institut für Sozialwissenschaften

Country

Germany

City

Cologne

Postal Code

50667

Street

Unter Sachsenhausen 6-8

Where to apply

Website

https://www.hidden-professionals.de/HPv3.Jobs/gesis/stellenangebot/32083/PhD-Ca…

Contact

City

Cologne

Website

http://www.gesis.org/home/

Street

Unter Sachsenhausen 6-8

Postal Code

50667

E-Mail

[email protected]

STATUS: EXPIRED