Job offer

· Developing neural retrieval and ranking models to support the effective retrieval of scientific literature from large-scale scientific article repositories like PubMed. · Advancing research in retrieval-augmented generation (RAG) to support the qualitative and quantitative synthesis of scientific evidence. · Investigating new ways to robustly and reliably evaluate domain-specific IR and RAG approaches to ensure that methods align with user expectations and preferences. · Collaborating with colleagues and international peers on research projects related to those listed above. · Publishing high-quality papers and presenting the results at leading IR and NLP conference venues.

· A completed M.Sc. degree in computer science, machine learning, and related fields. · Strong proficiency in English (the working language of the institute). · Capability and willingness to work independently and collaboratively.

Preferred Qualifications: · Good technical understanding of transformer language models. · Good understanding of IR fundamentals. · Good experience using machine learning libraries like PyTorch., Master Degree or equivalent

Languages ENGLISH