PhD position in Agent/LLM-based Evidence-based Reasoning (IDIAP - Switzerland)
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How to make LLM-based models capable of rigorous, fact-based inference? -
How to build AI models which can make sense of large-scale complex evidence?
This is an exciting opportunity to work at the interface between Large Language Models (LLMs) and complex reasoning.
The project:
LLMs have defined the foundations for the construction of models which can interpret and reason over language at scale. However, technical challenges remain in delivering models which are capable of factually correct, controlled and rigorous reasoning, fundamental in critical domains of applications such as biomedicine and policy-making.
In this project, we will work on the development of novel natural language inference (NLI) paradigms which can jointly reason over qualitative and quantitative evidence at scale. The project will focus on areas such as: (i) the development of new reasoning planning models for evidence-based reasoning and (ii) the integration of NLI models with statistical, causal and mechanistic inference paradigms.
The candidate will work at the Neuro-symbolic AI Group at IDIAP and will also be affiliated with the EPFL PhD programme.
This is a 4-year position funded by the SNSF-FAPESP RATIONAL project in collaboration with Daniel Pedronette (UNESP).
Candidates are expected to have:
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A BSc/MSc degree in Computer Science or related areas. -
Previous academic or industrial project experience in NLP (evidenced by project results and papers). -
Be confident in software development and in developing complex NLP experimental pipelines.
Interested applicants please send your CV to andre.freitas@idiap.ch by December 31st.