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

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 thrives on collaborative efforts across various disciplines, combining expertise in medicine, biology, computer science, and data science.

We are currently seeking a scientific assistant to join our dynamic team and contribute to interdisciplinary research partnerships. The anticipated start date for this position is March 1, 2026.

About the Project

Traumatic spinal cord injury (SCI) significantly impacts the lives of affected individuals and their families. A major challenge in predicting long-term recovery lies in the considerable variability of patient outcomes, which traditional clinical assessments may not adequately capture. Standard neurological evaluations often miss the underlying biological and functional diversity, hindering prediction accuracy and treatment strategies.

This project aims to close this gap by integrating neurological assessments with neurophysiological measurements and routine blood biomarkers, utilizing advanced machine learning techniques to combine these diverse data sources. By identifying the most informative clinical features, our approach seeks to deliver more accurate and interpretable recovery predictions, ultimately supporting better 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, available from the project's outset.
• Develop Advanced Deep Learning Models: Design and implement a multi-branch neural network that integrates 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

• 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.
• Proficiency in collaborative coding practices, version control (e.g., Git), and experience working on computing clusters.
• Prior experience with SCI data or related research topics is advantageous.
• A background in biomedical projects and experience in interdisciplinary collaboration is a plus.
• A commitment to scientific excellence and motivation to work within a diverse team.
• Proficiency in both written and spoken English.

We offer a 1-year project-based contract at the BMDS Lab with an 80% workload, providing a stimulating, collaborative environment within ETH Zurich, one of the world's leading universities in science and technology.

What We Offer

• A chance to contribute to pioneering biomedical data science with direct clinical relevance.
• Opportunities to enhance your skills in data science, machine learning, and neuroinformatics through practical applications addressing critical health conditions with a focus on SCI.
• Be a part of a highly motivated, multidisciplinary, and collaborative team.
• Learn from industry experts and contribute to an active research lab.

Application Instructions

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

Contact Information

If you have questions regarding the position, please reach out to Dr. Olga Taran at olga.taran@hest.ethz.ch (no applications).

For more information about the BMDS Lab, please visit our website.