Fully-funded PhD position “Computer Science: Knowledge Graphs & Natural Language Processing” (m/f/d), Leibniz University Hannover, Germany
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Jennifer D'Souza
Aug 14, 2023, 2:49:03 AM8/14/23
to NAACL-Latin-America
Dear colleagues and friends,
The Research Center L3S invites applications for the position of a Research Associate / PhD Candidate (m/f/d) “Computer Science: Knowledge Graphs & Natural Language Processing” (Salary Scale 13 TV-L; 100 %) starting at the earliest possible date. The position is limited to 3 years with the possibility of extension. The regular weekly working time is 39.8 hours (full-time).
Description:
The PhD topic will be in the context of the HybrInt project and the Open Research Knowledge Graph (https://orkg.org/) focusing on building knowledge graphs for the agricultural domain. The aim of these projects is to research and develop NLP solutions as large language models (LLMs) for crowdsourcing, representing and managing semantically structured, rich representations of scholarly contributions and research data in knowledge graphs and thus develop a novel model for scholarly communication. In the context of the PhD thesis you will be responsible for building and maintaining the ORKG data ingestion and processing pipelines to ensure the flow of high-quality semantified resources from academic publications. Your main responsibility in this position will be to build scalable solutions that crawl, ingest, process publications, and thereby enrich the ORKG. You will work alongside the ORKG engineering team to setup the AI/NLP ecosphere.
The tasks will focus on:
* Working in the areas of Natural Language Processing (text mining, information extraction, information retrieval/search) and Machine Learning of scholarly communication media (digital) data
* Research and development of suitable Large Language Models (LLMs) as NLP solutions
* Conceptually designing, modeling, and implementing data-driven services in one or more areas of information retrieval and extraction, data enrichment, and linking of data
Application Deadline: 15.09.2023
Web Address for Applications: https://www.uni-hannover.de/en/jobs/id/6435/ (en); https://www.uni-hannover.de/de/jobs/id/6435/ (de)
Yours cordially,
Jennifer
The Research Center L3S invites applications for the position of a Research Associate / PhD Candidate (m/f/d) “Computer Science: Knowledge Graphs & Natural Language Processing” (Salary Scale 13 TV-L; 100 %) starting at the earliest possible date. The position is limited to 3 years with the possibility of extension. The regular weekly working time is 39.8 hours (full-time).
Description:
The PhD topic will be in the context of the HybrInt project and the Open Research Knowledge Graph (https://orkg.org/) focusing on building knowledge graphs for the agricultural domain. The aim of these projects is to research and develop NLP solutions as large language models (LLMs) for crowdsourcing, representing and managing semantically structured, rich representations of scholarly contributions and research data in knowledge graphs and thus develop a novel model for scholarly communication. In the context of the PhD thesis you will be responsible for building and maintaining the ORKG data ingestion and processing pipelines to ensure the flow of high-quality semantified resources from academic publications. Your main responsibility in this position will be to build scalable solutions that crawl, ingest, process publications, and thereby enrich the ORKG. You will work alongside the ORKG engineering team to setup the AI/NLP ecosphere.
The tasks will focus on:
* Working in the areas of Natural Language Processing (text mining, information extraction, information retrieval/search) and Machine Learning of scholarly communication media (digital) data
* Research and development of suitable Large Language Models (LLMs) as NLP solutions
* Conceptually designing, modeling, and implementing data-driven services in one or more areas of information retrieval and extraction, data enrichment, and linking of data
Application Deadline: 15.09.2023
Web Address for Applications: https://www.uni-hannover.de/en/jobs/id/6435/ (en); https://www.uni-hannover.de/de/jobs/id/6435/ (de)
Yours cordially,
Jennifer
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