We are hiring an AI Software Engineer (100%)

Mon, 18 May 2026 00:00:00 +0000

Department of Quantitative Biomedicine — Start of employment to be determined

We are looking for an AI Software Engineer with a passion for tackling medical problems to help us create real-world AI tools in the medical field, particularly in Radiology and Cancer research. You will join a group of Medical AI researchers in the Krauthammer Lab and will have the opportunity to collaborate with multiple research teams at the University Hospital of Zurich and the University of Zurich.

You will be someone who loves to code and build high-performance, working systems. You are used to translating research breakthroughs into reliable, production-grade software. You will have experience with the software development life cycle, with a strong emphasis on implementation, deployment, testing, and continuous release. You will also have extensive knowledge and experience in LLMs.

You can see more about who we are and how we work here: krauthammerlab.ch

Responsibilities

In this position, you will be working at the heart of our Medical Language Technology Team, helping us work on the automatic generation of medical reports from medical images and convert unstructured medical text to structured information. Your primary focus will be on creating high-quality, production-ready code and taking end-to-end ownership of our machine learning and deployment pipelines. This would include the following:

Design, implement, and deploy scalable Multimodal Multilingual AI algorithms and models into production environments.
Architect and optimize models for reliable deployment in a web application context, turning research prototypes into robust, working solutions.
Develop and maintain robust, high-quality production pipelines (MLOps).
Contribute to a high-quality codebase, ensuring comprehensive testing and documentation.
Adapting and integrating “off-the-shelf” solutions for our research projects.
Pre-processing, post-processing, and annotation of data to support production systems.
Develop and train large multimodal AI models for pressing medical data.

The successful applicant will contribute to projects such as:

RadVLM — Conversational Vision-Language Model for Radiology.
RADICAL — Radiology AI-Driven Clinical Decision-Making with Multi-Modal Exploration.

Minimum Qualifications

Education

M.Sc. in Machine Learning, Computer Science, Applied Mathematics, Computational Science, or a related field, or equivalent experience.

Experience

At least +3 years of experience in Machine Learning, Computational Linguistics, and/or other relevant fields.
Expertise in large AI models (i.e., LLM, VLM, etc.), computational methods, data analysis, software and algorithm development, and modeling.
Demonstrated ability to transition research models into scalable, production systems.
Capable of building, deploying, and maintaining user-facing APIs that expose a range of AI features as a service.
Expert-level coding skills in Python, with a strong passion for the software development and MLOps side of AI.
Extensive experience in using modern deep learning frameworks (PyTorch, Hugging Face) and proficiency with software development and deployment tools (e.g., Git, Linux, containerization via Docker/Singularity, and GPU cluster management like Slurm).
Ability to do original and outstanding research in computational sciences and its relevant field.
Ability to work well independently as well as in a collaborative team environment, in-person as well as via online channels.
Ability to handle multiple projects at the same time.
Ability to present research and other types of work, internally and externally.

How to apply

Please prepare the following application materials:

CV with publication list or sample project descriptions.
If you are selected for the second interview, two (2) letters of recommendation should be submitted confidentially by the letter writers to michael.krauthammer@uzh.ch.

Applications can be submitted through the official UZH job listing here .

Studentische Hilfskraft (m/w/d) 30–40%

Fri, 08 May 2026 00:00:00 +0000

Quantitative Biomedizin / Medizininformatik — Stellenantritt sofort oder nach Vereinbarung, befristet

Fachbereich: Medizininformatik – Annotation klinischer Berichte

Am Lehrstuhl für Medizininformatik der Universität Zürich (UZH) ist zum nächstmöglichen Zeitpunkt die Position als studentische Hilfskraft für die Annotation von medizinischen Texten zu besetzen. Die Anstellung im Stundenlohn ist befristet auf drei Monate.

Projektbeschreibung: Im Rahmen aktueller Forschungsprojekte im Bereich des Natural Language Processing (NLP) und der computergestützten klinischen Entscheidungsfindung entwickeln wir Algorithmen zur automatisierten Analyse von Patientenunterlagen. Ziel dieser Tätigkeit ist die präzise semantische Markierung (Annotation) von klinischen Berichten, um hochwertige Datensätze für das Training von Machine-Learning-Modellen zu generieren.

Aufgaben

Textannotation: Identifikation und Klassifikation von Entitäten (z. B. Daten, med. Abteilungen, etc.) in klinischen Berichten und Befunden.
Qualitätssicherung: Überprüfung und Korrektur bereits annotierter Daten auf Basis spezifischer Richtlinien.
Dokumentation: Mitarbeit bei der Verfeinerung von Annotationsleitfäden unter Berücksichtigung medizinischer Genauigkeit.
Vergütung: attraktives Honorar pro Stunde.
Flexibilität: Die Arbeitszeiten können nach Absprache sehr flexibel gestaltet und ideal mit dem Studium vereinbart werden.

Profil

Studienhintergrund: Laufendes Studium der Humanmedizin (idealerweise im klinischen Abschnitt); Studierende anderer Fachrichtungen können sich ebenfalls bewerben.
Sprachkenntnisse: Exzellente Deutschkenntnisse in Wort und Schrift (Niveau C2/Muttersprache), insbesondere Sicherheit in der medizinischen Terminologie.
Arbeitsweise: Hohes Mass an Konzentrationsfähigkeit, Präzision und Zuverlässigkeit.
IT-Affinität: Sicherer Umgang mit digitalen Tools.

Bewerbungen können über das offizielle UZH-Stellenportal hier eingereicht werden.