Data Science Internship - Artificial Intelligence Applied to Hospital Data - 100%

About the job

Company Description

With more than 13,000 employees representing 160 professions, the Geneva University Hospitals (HUG) are a reference institution at the national and international level. To learn more about our institution, take a few minutes to consult our 2025 retrospective by clicking here .

The Medical and Quality Directorate's mission is to guarantee the quality and safety of medical services offered by the Geneva University Hospitals. The Infection Prevention and Control Service (SPCI) is responsible for controlling and preventing infections and reservoirs of resistant microorganisms in the hospital environment. The service consists of infectious disease physicians with clinical and research functions, a team of specialized nurses, epidemiologists, data scientists, and IT specialists. The service is also a collaboration center of the World Health Organization (WHO) for infection prevention and control and antibiotic resistance.

Job Description

Antibiotic-resistant bacteria represent a major challenge for health systems. The Geneva University Hospitals develop innovative approaches combining hospital epidemiology, data science, and artificial intelligence to improve the early detection of patients carrying multi-resistant bacteria.

In this context, we are developing the SEARCH-AI project funded by the HUG Private Foundation, which aims to optimize targeted screening of carriers of multi-resistant bacteria (ESBL, CPE, VRE) at admission and during the hospital stay using machine learning models applied to clinical hospital data.

As part of your internship, you will participate in the development and evaluation of predictive models to identify patients at risk of carrying resistant bacteria.

Main tasks include:

pre-processing and structuring hospital clinical databases (patient records, microbiology, hospitalization histories);
Feature engineering from longitudinal medical data;
Development and comparison of machine learning models (penalized logistic regression, LASSO, tree models, XGBoost, etc.);
Evaluation of model performance and interpretability analysis (SHAP or similar methods);
Contribution to the documentation of the analytical pipeline;
Participation in scientific discussions with a multidisciplinary team (clinicians, epidemiologists, data scientists)

Depending on the project's progress, the internship may contribute to a scientific publication or a presentation at an international conference.

Qualifications

This internship is intended for final-year students (Master's or engineering school) specializing in data science, machine learning, bioinformatics and applied statistics, or computer science, and you must have an internship agreement.

You have a good command of Python or R for data analysis, knowledge of supervised machine learning, as well as a solid foundation in statistics and modeling.

You have experience handling large databases and a strong interest in AI applications in health or biomedicine. Additionally, experience with medical or biological data, knowledge in epidemiology or public health, and familiarity with model interpretability methods will be considered assets.

A good command of English is also desired.

Additional Information

• Start date: To be agreed
• Number of positions: 1
• Work rate: 100%
• Contract type: 6-month fixed-term contract subject to agreement
• Application deadline: 17.04.2026
• Contact for information: spci-secretariat@hug.ch

Your application file must include a motivation letter, your curriculum vitae, copies of diplomas and certificates required for the position, and the last 2 work certificates.

This announcement is addressed equally to women and men.

Only applications submitted via the recruitment platform will be considered. Paper and email applications will not be processed.