Join the Biomedical Data Science Lab
The Biomedical Data Science (BMDS) Lab is dedicated to exploring data-driven solutions for healthcare, particularly in the realm of neurological conditions such as spinal cord injury (SCI), lower back pain, neurodegenerative disorders, and neurological tumors. At the heart of our research lies interdisciplinary collaboration that harnesses the expertise of fields including medicine, biology, and computer and data science. We are currently seeking a scientific assistant to become an integral member of our expanding team and contribute to innovative research partnerships. The anticipated start date is March 1, 2026.
Project Overview
Traumatic spinal cord injury (SCI) presents profound, lifelong challenges for affected individuals and their families. One major hurdle in predicting long-term recovery stems from the significant variability in patient outcomes, which conventional clinical assessments may not fully encapsulate. Standard neurological evaluations alone often fall short of reflecting the underlying biological and functional diversity, thus impeding both prediction accuracy and treatment strategy efficacy. Our project addresses this by merging neurological assessments with neurophysiological measurements and routine blood biomarkers, employing advanced machine learning techniques to synthesize these varied data sources. This approach aims to identify the most informative clinical features, yielding more accurate and interpretable recovery predictions and facilitating better patient stratification 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. These datasets will be readily available at the project’s inception.
- Develop Advanced Deep Learning Models: Design and implement a multi-branch neural network capable of integrating multiple data modalities into a cohesive 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
- You hold a Master's degree in Computer Science, Data Science, Biomedical Engineering, or a related field.
- You possess strong Python programming skills and have a demonstrated history of developing and training machine learning and deep learning models using Keras/TensorFlow and/or PyTorch, supported by experience in statistical data analysis.
- You are familiar with collaborative coding practices, version control (e.g., Git), and have experience working on computing clusters.
- Experience with SCI data or related research topics is advantageous.
- A background in biomedical projects and experience in interdisciplinary collaboration are bonuses.
- You are motivated to work as part of a diverse team and are dedicated to scientific excellence in your field.
- You are proficient in both written and spoken English.
What We Offer
- A 1-year project-based contract at the BMDS Lab with an 80% workload.
- A stimulating and 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.
- Advancement in your skills in data science, machine learning, and neuroinformatics applied to critical health conditions, particularly focusing on SCI.
- An invitation to be part of a highly motivated, multidisciplinary, and collaborative team.
- The chance to learn from experts in the field and actively contribute to a vibrant research lab.
Application Process
Apply online using the form below. Only applications matching the job profile will be considered.
For those wishing to learn more about the BMDS Lab, further information can be found on our website.
If you have any questions regarding the position, please reach out to Dr. Olga Taran via email at olga.taran@hest.ethz.ch (please refrain from submitting applications via email).