Job Opportunity: Scientific Assistant at the Biomedical Data Science (BMDS) Lab
The Biomedical Data Science (BMDS) Lab is at the forefront of exploring data-driven solutions for healthcare, particularly focusing on neurological conditions such as spinal cord injury (SCI), lower back pain, neurodegenerative disorders, and neurological tumors. Our research is built on a foundation of interdisciplinary collaboration, uniting expertise in medicine, biology, computer science, and data science. We are looking for a scientific assistant to join our growing team and contribute to impactful interdisciplinary research partnerships. The anticipated start date is March 1, 2026.
About the Project
Traumatic spinal cord injury (SCI) has profound and lifelong consequences for affected individuals and their families. A significant challenge in predicting long-term recovery is the considerable variability in patient outcomes that traditional clinical assessments may not fully capture. Standard neurological evaluations alone cannot reflect the underlying biological and functional diversity, limiting both prediction accuracy and the effectiveness of treatment strategies. This project aims to bridge this gap by:
- Integrating neurological assessments with neurophysiological measurements and routine blood biomarkers.
- Utilizing advanced machine learning techniques to combine these diverse data sources.
- Identifying the most informative clinical features to enhance recovery predictions, aiding in patient stratification, prognosis, and personalized treatment strategies.
Key Responsibilities
- Explore and Manage SCI Datasets: Work with international databases of SCI patient data, ensuring accurate handling, preprocessing, and integration of heterogeneous clinical, neurophysiological, and biomarker information.
- Develop Advanced Deep Learning Models: Design and implement a multi-branch neural network capable of integrating multiple data modalities into a unified representation.
- Implement a Multi-Task Learning Framework: Build and evaluate models that predict multiple related recovery outcomes simultaneously, leveraging shared information between tasks to enhance predictive performance, interpretability, and generalization.
Qualifications
- A Master's degree in Computer Science, Data Science, Biomedical Engineering, or a related field.
- Strong Python programming skills with a proven track record in developing and training machine and deep learning models using Keras/TensorFlow and/or PyTorch, complemented by experience in statistical data analysis.
- Experience with collaborative coding practices, version control (e.g., Git), and working in computing clusters.
- Familiarity with SCI data or related research topics is an advantage.
- A background in biomedical projects and experience in interdisciplinary collaboration is a plus.
- A desire to work as part of a diverse team, committed to scientific excellence.
- Proficient in both written and spoken English.
What We Offer
- A 1-year project-based contract at the BMDS Lab (80% workload).
- A stimulating, collaborative environment within ETH Zurich, one of the world’s leading universities for science and technology.
- The opportunity to contribute to cutting-edge biomedical data science with direct clinical relevance.
- Develop your skills in data science, machine learning, and neuroinformatics through applications to critical health conditions, particularly focusing on SCI.
- Be part of a highly motivated, multidisciplinary, and collaborative team.
- Learn from experts in the field and contribute to an active research lab.
We invite you to apply online using the form below. Please ensure that your application includes:
- Curriculum Vitae (CV): outlining your educational background, previous positions, and (if applicable) publications.
- Task-based statement (maximum 1 page): briefly describe how you would approach the integration of longitudinal multi-assessment data for recovery prediction after SCI.
- Contact information for two references.
Only applications matching the job profile will be considered.
For further information about the BMDS Lab, please visit our website.
For inquiries regarding the position, please contact Dr. Olga Taran at olga.taran@hest.ethz.ch (no applications).