Scientific Assistant in Biomedical Machine Learning and Data Science / Scientific Assistantess in Biomedical Machine Learning and Data Science

Join the Biomedical Data Science (BMDS) Lab

The Biomedical Data Science (BMDS) Lab is at the forefront of exploring data-driven solutions for healthcare applications, specifically focusing on neurological conditions such as spinal cord injury (SCI), lower back pain, neurodegenerative disorders, and neurological tumors. Our research thrives on interdisciplinary collaboration, melding expertise from medicine, biology, computer science, and data science. We invite applications for a Scientific Assistant to join our expanding team and engage in impactful interdisciplinary research partnerships, with an anticipated start date of March 1, 2026.

About the Project

Traumatic spinal cord injury (SCI) has profound and lifelong effects on both individuals and their families. A significant challenge in predicting long-term recovery is the substantial heterogeneity in patient outcomes, which traditional clinical assessments may fail to capture fully. Standard neurological evaluations often do not reflect the underlying biological and functional diversity, limiting 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, we will analyze these diverse data sources to identify the most informative clinical features. Our objective is to deliver more accurate and interpretable recovery predictions, supporting improved patient stratification, prognosis, and personalized treatment strategies.

Your Responsibilities

• Data Management: Explore and manage SCI datasets by collaborating with international databases, ensuring precise handling, preprocessing, and integration of heterogeneous clinical, neurophysiological, and biomarker information.
• Model Development: Design and implement advanced deep learning models, specifically multi-branch neural networks that integrate multiple data modalities into a cohesive representation.
• Multi-Task Learning: Construct and evaluate models that predict various related recovery outcomes simultaneously, leveraging shared information between tasks to enhance predictive performance, interpretability, and generalization.

Your 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 experience developing and training machine learning and deep learning models using Keras/TensorFlow and/or PyTorch, complemented by a background in statistical data analysis.
• You are familiar with collaborative coding practices, version control systems (such as Git), and have experience working on computing clusters.
• Experience in SCI data or related research topics is a plus, as is a background in biomedical projects and interdisciplinary collaboration.
• You are motivated to work as part of a diverse team, committed to scientific excellence, and 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 institutions for science and technology.
• The opportunity to contribute to cutting-edge biomedical data science with direct clinical relevance.
• Advancement of your skills in data science, machine learning, and neuroinformatics through biomedical applications directed toward critical health conditions, particularly focusing on SCI.
• The chance to be part of a dedicated, multidisciplinary, and collaborative team, learning from experts while contributing to an active research lab.

Apply online using the form below. Please note that only applications matching the job profile will be considered. We look forward to reviewing your submission!

Contact Information

For further details about the BMDS Lab, please visit our website. If you have any questions regarding the position, feel free to reach out to Dr. Olga Taran at olga.taran@hest.ethz.ch. Please note that we do not accept applications via email.