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The Biomedical Data Science Lab at ETH Zurich investigates data-driven solutions for healthcare applications, focusing on neurological conditions and systemic infections such as sepsis. This position offers an excellent opportunity to work at the forefront of biomedical data science, contributing to key projects in biomedical imaging and clinical research.
Tasks
- Conduct statistical and machine-learning analyses using EMSCI and related SCI datasets.
- Develop and validate predictive models of neurological recovery and functional outcomes after SCI.
- Perform data preprocessing, quality control, harmonisation, feature engineering, and exploratory data analysis.
- Apply appropriate statistical methods, including regression, longitudinal data analysis, survival analysis, and machine-learning approaches.
- Develop reproducible analytical workflows in R and/or Python.
- Contribute to scientific publications, reports, presentations, and grant applications.
- Collaborate with clinicians, neuroscientists, statisticians, and data scientists across participating SCI centres.
- Support the organisation and coordination of scientific meetings, workshops, consortium meetings, and other research activities, including scheduling, preparation of agendas and materials, communication with participants, and follow-up.
- Assist with the coordination of ongoing collaborative projects and follow-up of scientific activities and deliverables.
Requirements
- MSc or equivalent degree in statistics, biostatistics, data science, biomedical engineering, computer science, epidemiology, neuroscience, or a related discipline.
- Strong background in statistics and/or machine learning.
- Experience working with longitudinal and/or clinical datasets.
- Strong programming skills in R and/or Python.
- Experience with statistical modelling, data visualisation, and reproducible research.
- Familiarity with machine-learning methods such as random forests, gradient boosting, neural networks, or related approaches.
- Previous experience working with EMSCI data or other large SCI databases is highly desirable.
- Knowledge of SCI-specific clinical and neurological outcome measures (e.g., ISNCSCI/ASIA, SCIM) is an advantage.
- Experience working with multicentre clinical datasets is an advantage.
- Fluent in English and proficient in German, both written and spoken.
- Excellent organisational and communication skills.
- Ability to work independently and reliably while collaborating effectively in a multidisciplinary and international research environment.
- Interest in SCI research and the application of data science to clinical research.
Benefits
- An 80–100% position within the Biomedical Data Science Lab at ETH Zurich.
- The opportunity to work with EMSCI, one of the major longitudinal SCI research databases, and related international datasets.
- A highly interdisciplinary environment at the interface of clinical neuroscience, statistics, machine learning, and biomedical data science.
- Close interaction with leading SCI researchers and clinical centres in Switzerland and internationally.
- The opportunity to contribute to high-quality scientific publications and international collaborative projects.
- A varied role combining hands-on quantitative research with scientific coordination and project management.
- A stimulating research environment at ETH Zurich, with the lab based in Schlieren.
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Über uns
Die ETH Zürich ist eine technisch-naturwissenschaftliche Hochschule des Bundes mit Sitz in Zürich. Wir betreiben Lehre, Forschung und Wissenstransfer in Bereichen wie Ingenieurwissenschaften, Naturwissenschaften, Architektur, Mathematik, Informatik, Management sowie Sozial- und Geisteswissenschaften. Unsere Ausbildung umfasst Bachelor-, Master-, Doktorats- und Weiterbildungsangebote und ist eng mit internationaler Spitzenforschung verbunden. Als Teil des ETH-Bereichs entwickeln wir wissenschaftliche Grundlagen, Technologien und Lösungen für Gesellschaft, Wirtschaft und globale Herausforderungen.
Das Team
The Biomedical Data Science Team collaborates across disciplines, including medicine, biology, computer, and data science, and works closely with clinicians, neuroscientists, statisticians, and data scientists in Switzerland and internationally.