Scientific Assistant / Scientific Assistantess

Join the Biomedical Data Science Lab

The Biomedical Data Science (BMDS) Lab is dedicated to exploring data-driven solutions for healthcare applications, particularly focusing on neurological conditions such as spinal cord injury (SCI), lower back pain, neurodegenerative disorders, and neurological tumors. Our research emphasizes collaboration across various disciplines, merging expertise in medicine, biology, computer science, and data science. We are currently seeking a scientific assistant to join our growing team and contribute to interdisciplinary research partnerships. The anticipated start date is March 1, 2026.

About the Project

Traumatic spinal cord injury (SCI) significantly impacts the lives of affected individuals and their families, presenting long-term challenges. A key obstacle in predicting long-term recovery is the vast variability in patient outcomes, which traditional clinical assessments may not adequately capture. Standard neurological evaluations fail to reflect the biological and functional diversity inherent in these conditions, limiting both prediction accuracy and treatment efficacy.

This project aims to bridge this gap by integrating neurological assessments with neurophysiological measurements and routine blood biomarkers. Utilizing advanced machine learning techniques, we will combine these diverse data sources to identify the most informative clinical features. The goal is to provide more accurate and interpretable recovery predictions, enhancing patient stratification, prognosis, and personalized treatment strategies.

Key Responsibilities

• Data Management: Explore and manage SCI datasets by working with international databases of SCI patient data, ensuring accurate handling, preprocessing, and integration of diverse clinical, neurophysiological, and biomarker information.
• Model Development: Design and implement advanced deep learning models, specifically a multi-branch neural network that integrates various data modalities into a unified representation.
• Multi-task Learning: Build and evaluate models that predict multiple, related recovery outcomes simultaneously, leveraging shared information between tasks to enhance predictive performance, interpretability, and generalizability.

Qualifications

• Master's degree in Computer Science, Data Science, Biomedical Engineering, or a related field.
• Strong Python programming skills with demonstrated experience in developing and training machine and deep learning models using Keras/TensorFlow and/or PyTorch, accompanied by a background in statistical data analysis.
• Familiarity with collaborative coding practices, version control (e.g., Git), and experience working on computing clusters.
• Experience with SCI data or related research topics is advantageous.
• A background in biomedical projects and a track record of interdisciplinary collaboration is a plus.
• Motivated to work as part of a diverse team, committed to scientific excellence in your field.
• 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 premier universities for science and technology.
• The opportunity to engage in cutting-edge biomedical data science with direct clinical relevance.
• Advance your skills in data science, machine learning, and neuroinformatics through critical health applications, specifically focused on SCI.
• Be part of a motivated, multidisciplinary, and collaborative team.
• Learn from experts in the field and contribute to an active research lab.

Apply online using the form below. Only applications matching the job profile will be considered.

Contact Information

For any questions regarding the position, please contact Dr. Olga Taran via email at olga.taran@hest.ethz.ch (please do not submit applications via email).

Further information about the BMDS lab can be found on our website.