The project

Our Sinergia consortium unites expertise at the University of Zurich (Mathematical Modeling & Machine Learning) and ETH Zurich (Department of Mathematics) to push the frontier of data‑driven decision support in large‑scale, real‑world systems under SNSF project “From Single‑Disease Research to Informed Machine Learning. We develop methods that combine reinforcement learning (RL) and large language models (LLMs) to optimize processes, automate design choices and reason about constraints under uncertainty. We will appoint up to two post‑doctoral researchers, each specializing in one of the complementary tracks below. The precise application domain will be defined in consultation with the successful candidates and our research partners in epidemiology and related fields.

Your role

Track A – RL / Optimization

• Design, implement and evaluate RL frameworks for complex, high‑dimensional environments, leveraging simulation‑based optimization and digital‑twin testbeds
  

• Explore multi‑agent or distributed training techniques to scale optimization across interacting subsystems
  

• Collaborate with domain scientists to translate algorithms into prototype decision‑support tools
  

Track B – LLM / Knowledge‑Engineering

• Develop and fine‑tune LLM pipelines that integrate structured reasoning tools (e.g. retrieval‑augmented generation, knowledge graphs, constraint parsers)
  

• Build workflows for transparent explanation and evaluation of model decisions
  

• Maintain and contribute to open‑source libraries that support reproducible research in the project