This opportunity is based in Bern and Zurich

Intelligent Document Retrieval (Master Thesis/ Internhips)


Modern search engines are constantly becoming more powerful and sophisticated allowing to index millions of documents and executing complex user queries in minimal time. Nevertheless, human intelligence and intervention is still needed to identify, interpret, extract and link relevant content from returned documents.


Recent advances in machine learning (ML) and natural language processing (NLP) have enabled us with promising tools and techniques for automating tasks, such as named entity recognition (NER), topic extraction, document categorization, query expansion, document recommendation, text summarization etc. The objective of the internship consists in designing, evaluating and implementing an ensemble of techniques, that complement/boost the capabilities of existing state-of-the-art search engines and facilitate users in identifying, extracting and linking relevant information from various, often heterogenous, sources.


In this role

The candidate will pursue research and development and will engage in the following activities:

  • Concepting/Developing/Integrating an end-to-end solution
  • Designing/Evaluating multilingual models for various ML tasks
  • Delivering a productive proof of concept “as a Service”
  • Proofing business cases to answer market challenges  

What we offer

Join our team as intern and you will find a young, dynamic and culturally diverse working environment.

About your profile

  • Interest in machine learning, data science, natural language processing and information retrieval
  • Software engineering and programing skills (Python/Java, Linux)
  • Very good language skill of English and either French or German
  • Experience with the Elastic Stack (ELK), Kafka and Scrapy is a plus

If you are INTERESTED in applying for this position, please send us your complete application (CV, cover letter, letter of reference, diplomas and certificates).

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