Michael Moor

A fully funded PhD position is available in the group of Assistant Professor Michael Moor at ETH Zurich, Department of Biosystems Science and Engineering (D-BSSE), located in Basel, Switzerland. The doctoral student will work on cutting-edge research in medical reasoning, leveraging machine learning and artificial intelligence methodologies. The position is part of the EU-funded Marie-Curie project "MLCARE," offering a unique opportunity to contribute to interdisciplinary research at the intersection of computer science, medical science, and life sciences. The group is embedded in the vibrant life science hub of Basel and is actively involved with the ETH AI Center and SwissAI projects. State-of-the-art GPU clusters and computational resources are available to support research activities. The successful candidate will join a dynamic and international research environment, collaborating with leading experts in AI and medical informatics. Applicants should have a strong background in computer science, machine learning, artificial intelligence, or related fields. Experience with medical reasoning, life sciences, or high-performance computing is a plus. Candidates must fulfill ETH Zurich's doctoral admission requirements, which typically include an excellent academic record, a relevant degree (usually a master's), and proficiency in English. The ability to work in interdisciplinary teams and a high level of motivation are essential. The position is fully funded through the Marie-Curie program, covering salary and research expenses according to EU and ETH Zurich standards. The application process is managed through the ETH Zurich online portal, and candidates are encouraged to apply early as the position may close once filled. For more information on the application process, refer to the ETH Zurich FAQ page. Keywords: machine learning, medical reasoning, artificial intelligence, life sciences, GPU computing, Marie-Curie, AI Center, SwissAI, doctoral student, medical informatics.

ETH Zurich is inviting applications for a postdoctoral research position focused on "Language Models for Pediatric Data Analysis" in collaboration with the University Children's Hospital Basel. The successful candidate will join the Medical AI Lab at ETH Zurich (D-BSSE, Basel) and work closely with clinicians, clinical coders, and IT infrastructure teams to develop, validate, and safely deploy large language models (LLMs) for automated coding of pediatric diagnoses from electronic health records (EHRs). The project aims to enhance research capabilities and clinical data usability through advanced machine learning and artificial intelligence techniques. The position is embedded in a vibrant interdisciplinary environment, with access to the ETH AI Center and SwissAI initiative, providing opportunities for collaboration and professional growth. The role involves model development, rigorous validation on new benchmarks, and safe deployment of locally hosted LLMs. Additional responsibilities include publishing research results in top-tier venues and contributing to the group’s engagement with the broader AI and medical informatics communities. Applicants should have a PhD in Computer Science, Medical AI, Medical Informatics, or a closely related field. Required skills include strong programming abilities in Python, experience with modern ML/AI/LLM stacks (such as PyTorch, HuggingFace, Ollama, vllm), and proficiency in German at C1 level or higher for analyzing local patient records. Experience with clinical NLP, retrieval-augmented generation (RAG), vector databases, Docker, GPU-based infrastructure, and medical data coding (ICD-10) is highly desirable. Candidates should demonstrate good computational engineering practices and the ability to work both independently and collaboratively in a diverse team. Effective communication in English and German is essential. The position is fully funded and offers access to state-of-the-art computational resources, including large GPU clusters, and direct clinical collaborations. ETH Zurich is committed to diversity, equality of opportunity, and sustainability, fostering an inclusive and supportive environment for all staff and students. To apply, candidates must submit their application online via the ETH Zurich application portal, including a CV, Bachelor and Master transcripts, a motivation letter, and letters of recommendation (or a list of referees). Applications sent via email or postal services will not be considered. For further information about the research group, visit the provided academic page. Questions regarding the position can be directed to Prof. Michael Moor’s lab email (no applications via email). Keywords: Language Models, Pediatric Data Analysis, Medical AI, Clinical NLP, Electronic Health Records, Machine Learning, Artificial Intelligence, Biomedical Informatics.

ETH Zurich is advertising a Postdoctoral Researcher position in Multimodal Reasoning Models for Oncology within the Medical AI Lab led by Michael Moor at the D-BSSE in Basel, in collaboration with Kaiko.ai and clinical partners. The project focuses on developing, post-training, and evaluating flexible AI systems for oncology that combine language models, vision, biomedical knowledge, clinical context, and patient-level multimodal data . Research topics include foundation models , multimodal language model architectures , retrieval from literature and clinical guidelines , tool-augmented inference , multi-agent workflows , process supervision , verifier-guided training , and reinforcement learning-based post-training . The role is designed for a highly motivated researcher who wants to work on clinically grounded AI for diagnosis, molecular interpretation, treatment selection, longitudinal care, uncertainty calibration, abstention, and safety-aware reasoning. The position emphasizes traceable, auditable outputs and evaluation in clinically realistic settings, including guideline concordance, diagnostic and therapeutic reasoning quality, tool-use reliability, citation quality, and clinician-in-the-loop assessment. Eligibility: applicants must hold a PhD in Computer Science, Machine Learning, Medical AI, Biomedical Informatics, Computational Biology, or a related field. Strong Python and modern ML framework skills are required, along with experience in deep learning and large language models. A strong publication record in AI/ML or related biomedical fields is expected. Preferred experience includes multimodal models, biomedical/clinical language models, reasoning agents, LLM post-training, retrieval methods, and scalable GPU training. Funding and environment: this is a full-time postdoctoral position at ETH Zurich with competitive salary and excellent research infrastructure. The group has access to large-scale GPU resources through SwissAI projects, including the Alps cluster, and offers a highly interdisciplinary environment spanning AI, oncology, and clinical informatics. Application: submit your application only through the ETH Zurich online portal. The application package should be combined into one PDF and include a CV with significant publications, Bachelor and Master transcripts, a motivation letter, and letters of recommendation if available. The group plans to collect applications for about one month, with the stated deadline of 19 July .