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Knowledge Engineering Intern (Lausanne, CH) @ nestleHRprdRMK

Lausanne, Vaud, CHOnsiteInternship
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About this role

Location: Lausanne, Switzerland Contract type / duration: Internship – 6 months Activity rate: 100% Start date: February / March 2027 Be a force for good and transform your potential into something extraordinary.

As a Knowledge Engineering Intern at Nestlé Research , your mission will be to explore and assess ontologies, vocabularies and knowledge models related to chemical contaminants, with a particular focus on food safety. You will join the Institute of Food Safety and Analytical Sciences and work at the intersection of data science, knowledge representation and domain modelling. By collaborating with domain scientists and computational specialists, you will help establish reusable semantic foundations that improve data harmonisation, interoperability and knowledge management.

This internship offers an opportunity to combine research, technical development and scientific collaboration while gaining practical experience with semantic technologies and their application to chemical and food safety data. How you’ll make an impact as a Knowledge Engineering Intern Review state-of-the-art ontologies, vocabularies and knowledge graphs related to chemical contaminants and food safety, and assess relevant publicly available standards and semantic frameworks Evaluate how external semantic resources can be reused, extended or mapped to internal data models, business concepts and analytical needs Identify gaps in existing knowledge models by collaborating with domain scientists and propose approaches to improve data harmonisation and interoperability Develop proof-of-concept tools for selected ontology-driven use cases using appropriate programming and semantic web technologies Document your findings and present clear, evidence-based recommendations on how semantic resources could support future knowledge management initiatives What will make you successful Student or recent graduate from a Bachelor or Master degree in Computer Science, Computer Engineering, Data Science, Artificial Intelligence or a related field Strong Python programming and data-processing skills, with the ability to develop structured and reusable technical solutions Familiarity with semantic web technologies such as RDF, RDFS, OWL and SPARQL, as well as knowledge graphs, ontology engineering, linked data or data modelling concepts is a strong plus Interest in applying data science and knowledge engineering to chemical, food safety or food quality topics; experience working in Unix or Linux environments is an advantage Strong analytical, problem-solving and communication skills, with curiosity, autonomy and a collaborative mindset Fluency in English (written & spoken) At Nestlé Research, we use science, technology and collaboration to address complex challenges and contribute to the development of safe, high-quality food and nutrition solutions.

Our benefits are designed to support your growth and wellbeing, so you can thrive at work and in life: Learning and development opportunities to grow your career Healthcare contribution and access to the Employee Assistance Program Attractive employee discounts across various products and services What to expect from our hiring process We are committed to an inclusive and respectful hiring experience and are happy to provide reasonable accommodation if needed.

Our workplaces are fully accessible and supported by a strong safety culture, with modern installations and procedures to ensure a safe environment for everyone.

The hiring process typically includes a video interview with Talent Acquisition, an interview with the hiring team, and a final discussion and offer.

We review applications as they are received and may close the role once a strong list of relevant candidates has been identified, so we encourage you to apply early.

All information is treated confidentially.

Ready to start your career journey with us? Apply now and transform your potential into something extraordinary.

Skills

PythonRDFOWLSPARQLknowledge graphontology engineeringData ModelingUNIXLinuxData ScienceFood Safetyfood quality

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