Postdoctoral Researcher in Multimodal Reasoning Models for Oncology — ETH Zürich
NewCHF 62'000 - 94'000
ETH Zürich · Basel (BS)
- Location
- Basel
- Contract
- fixed-term
- Posted
- Yesterday
SalaryCHF 62'000 - 94'000
Role overview
Postdoctoral Researcher in Multimodal Reasoning Models for Oncology
100%, Basel, fixed-term print Drucken
We are seeking an exceptional and highly motivated Postdoctoral Researcher to lead research on multimodal reasoning models for oncology.
- Postdoctoral Researcher in Multimodal Reasoning Models for Oncology
- 100%, Basel, fixed-term print Drucken
Additional details
- 100%, Basel, fixed-term
- This position is embedded within a highly interdisciplinary collaboration between ETH Zurich, Kaiko.ai, and clinical partners, offering an opportunity to advance foundational AI research while working toward real-world translation in oncology. Reasoning Models for Oncology
- Development and adaptation of oncology-focused foundation models capable of reasoning over complex clinical questions, including diagnosis, molecular interpretation, treatment selection, and longitudinal care. Multimodal language model architectures
- Development of uncertainty-aware and safety-aware reasoning behavior Reasoning Strategies, Agents, and Tool Use
- Development of model workflows that can use external tools and knowledge sources in a reliable and auditable way.
- Citation-grounded and traceable outputs suitable for expert review Process Supervision and Post-Training
- Calibration, abstention, and safety-aware optimization Clinical Evaluation and Safety
- Evaluation of oncology reasoning models in clinically meaningful settings. Key evaluation dimensions include: Guideline concordance
- Diagnostic and therapeutic reasoning quality Molecular interpretation accuracy Tool-use reliability Citation quality and evidence grounding
- Trace auditability and clinician-in-the-loop evaluation
Notes and original content
- This position is embedded within a highly interdisciplinary collaboration between ETH Zurich, Kaiko.ai, and clinical partners, offering an opportunity to advance foundational AI research while working toward real-world translation in oncology.
- Job description
- Reasoning Models for Oncology
- Development and adaptation of oncology-focused foundation models capable of reasoning over complex clinical questions, including diagnosis, molecular interpretation, treatment selection, and longitudinal care.
- This may include:
- Multimodal language model architectures
- Development of uncertainty-aware and safety-aware reasoning behavior
- Reasoning Strategies, Agents, and Tool Use
- Examples include:
- Citation-grounded and traceable outputs suitable for expert review
