**Postdoctoral researcher positions focused on the use of advanced AI techniques such as reinforcement learning and large language models for complex system optimi-zation**:
**80%-100%, fixed-term**:
**Job description**:
**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
**Both tracks**will co‑supervise doctoral students, publish in leading venues, and contribute to open‑source tooling.
**Profile**:
**Must have (both tracks)**
- PhD (or equivalent) in computer science, applied mathematics, operations research, physics, statistics or a related field
- Excellent Python skills and familiarity with modern ML stacks (e.g. PyTorch, JAX, Hugging Face)
- Ability to thrive in an interdisciplinary environment and to communicate complex ideas clearly
**Nice to‑have - Track A**
- Experience with simulation‑based optimization or digital‑twin frameworks
- Familiarity with multi‑agent RL or distributed training
**Nice to have - Track B**
- Experience integrating LLMs with structured reasoning tools (RAG, KGs, constraint solvers)
- Track record of open‑source contributions to RL, LLM or optimization libraries
**Workplace**:
**Workplace**:
**We offer**:
- **Fully funded positions (SNSF postdoctoral scale, approx. CHF 100k/year)** within a vibrant, international research environment
- Mentoring by** Nicola Serra (Mathematical Modeling & ML, UZH)** and Alessio **Figalli (Mathematics, ETHZ)**, together with the broader Sinergia team
- Close collaboration with partners in medicine, economics and computer science
- State‑of‑the‑art computing resources, a generous travel & training budget, and support for industry or clinical secondments
- A dynamic, family‑friendly workplace in Zurich with competitive Swiss salaries and an excellent quality of life
**Curious? So are we.**:
- CV
- Publication list
Further information