🎯 What You’ll Do

• Support preprocessing, feature engineering, and cleaning of real-world clinical/hospital datasets
• Contribute to the development and evaluation of time-series and tabular ML models for early sepsis detection and clinical deterioration
• Assist in exploratory data analysis and data visualization for model interpretability and research output
• Collaborate with data scientists and clinicians to help validate findings and interpret model outputs
• Contribute to model documentation, reproducibility pipelines, and clinical study materials
• Present results in team meetings and, where possible, support publications or conference submissions

About You

• Currently enrolled in (or recently completed) a degree in Computer Science, Data Science, Biomedical Engineering, Applied Mathematics, or similar
• Solid Python skills, especially in pandas, scikit-learn, matplotlib/seaborn, and Jupyter
• Familiarity with ML/AI concepts (classification, time-series models, evaluation metrics, cross-validation)
• Some experience with real-world or clinical data is a plus
• Interest in healthcare, clinical AI, and impactful technology
• You’re detail-oriented, eager to learn, and collaborative

🏢 Team Culture

• We treat each other with respect, humility, and openness;
• We value curiosity, experimentation, and fast learning;
• We embrace flexibility and focus on solving real-world problems that matter;
• We believe in diversity—of background, perspective, and skill set;
• We value open dialogue and brainstorming across multidisciplinary teams;
• We prioritize deep work, async collaboration, and only meet when it matters;
• Work from anywhere in the world (within ±3h of GMT), as long as the WiFi’s solid.

🎁 What We Offer

• Real-world impact: Work on AI that could save lives in hospital settings
• Mentorship and training from a highly experienced AI & product team
• Access to real clinical datasets and tools used in regulatory-grade AI development
• Flexible working hours and fully remote or hybrid setup
• Opportunity to grow into a longer-term role (e.g., thesis project, part-time associate, full-time role)