Lnds

<h3>Who we are</h3>Luxembourg National Data Service (LNDS) is a brand of PNED G.I.E. an organisation created by the Luxembourg Government, to implement Luxembourg’s strategies in research, innovation, and digitalisation. LNDS enables value creation from secondary use of data, for public and private partners and supports the sharing and re-use of public sector data, in a trustable manner. The LNDS service portfolio includes know-how, capabilities, tools, infrastructure, and data services. Through efficient &amp; responsible use of data and improving the secondary use of data, LNDS will support the acceleration of economic, ecological, and societal transitions.<h3>Purpose of the job / project</h3>You will work closely with LNDS’ Data Stewards, a multidisciplinary team covering topics of Research Data Management, Data Governance, and Applicant support in Data Access Applications.   You will contribute to accelerate and facilitate the LNDS role in supporting applicants for Data Access Requests.<h3>What you will do</h3>You will investigate the further development of an existing Large Language Model (LLM) pipeline based on Retrieval-Augmented Generation (RAG). The objective is to design, implement, and evaluate one or more approaches for schema-to-text and text-to-schema transformations within a defined Data Access Application workflow.  The developed system will:  <ul><li>Analyze data flow diagrams and populate the corresponding template with accurate and complete information.</li><li>Create data flow diagrams based on textual requirements and specifications.</li><li>Verify the internal consistency and logical coherence of data flows or generated outputs.</li><li>Perform compliance checks against reference materials and knowledge sources provided mainly through the RAG framework.</li><li>Identify opportunities to improve the quality, completeness, and consistency of data flows or generated outputs.</li></ul>  The basic business needs are:  <ul><li>To commit to developing an understanding of business goals and operational processes underlying the use case and translating them into effective AI-driven solutions. </li><li>To evaluate and validate the generated outputs against defined quality criteria and state-of-the-art assessment frameworks. </li></ul><h3>Who you are</h3><ul><li>Master's student in Mathematics, Computer Science, Data Science, or a related field</li><li>Ability to conduct literature reviews and select relevant publications</li><li>Critical thinking </li><li>Team-working ability</li><li>Technical expectations<ul><li>Understanding of machine learning concepts </li><li>Familiarity with evaluation methods and metrics Natural Language Processing (NLP)</li><li>Programming experience, including working with APIs</li><li>Experience with Open-Source LLMs is a plus</li><li>Familiarity with RAG concepts</li><li>Prompt design </li></ul></li></ul>

Technical Stewardship - 6-Month Internship

<h3>Who we are</h3>Luxembourg National Data Service (LNDS) is a brand of PNED G.I.E. an organisation created by the Luxembourg Government, to implement Luxembourg’s strategies in research, innovation, and digitalisation. LNDS enables value creation from secondary use of data, for public and private partners and supports the sharing and re-use of public sector data, in a trustable manner. The LNDS service portfolio includes know-how, capabilities, tools, infrastructure, and data services. Through efficient &amp; responsible use of data and improving the secondary use of data, LNDS will support the acceleration of economic, ecological, and societal transitions.<h3>Purpose of the job / project</h3>You will support an AI-plugged data space ecosystem project.  Context and motivation: the Data Space Support Centre (DSSC) coordinates the development of European data spaces and defines which standards a data space should use for interoperability, trust, and governance.<h3>What you will do</h3>This project intends to enable semantic and conceptual interoperability jobs by delegating to an LLM the task of checking for mappings of meanings and concepts, aligning semantic discrepancies framed as proposals or assertions before the final human review, and accepting a new, admissible data vocabulary enrichment. The AI semantic mapper automatises the search for plausible candidates across existing SKOS mappings. LLM is also involved in drafting the first-pass Data Contract.<h3>Who you are</h3><ul><li>Understanding of metadata standards</li><li>Familiarity with Python</li><li>Curiosity about open data ecosystems and metadata-driven data governance</li><li>Basic familiarity with any documentation tool (Markdown a plus)</li><li>Interest/knowledge in software development processes, version control systems (e.g., Git)</li><li>Eager to use new AI tools, and to test edge concepts gmail</li><li>Strong plus: Familiarity with:<ul><li>SPARQL, or JSON-LD for metadata manipulation and validation</li><li>Linked Data, ontologies or semantic web technologies</li><li>Strong written and communication skills in English</li><li>Ability to write clear, concise, well-structured content</li></ul></li></ul>

Lnds

Open jobs at Lnds

Technical Stewardship - 6-Month Internship

Data Engineering and Architecture - 6-Month Internship

Working for Lnds?

Featured companies