Scientific Assistant / Scientific Assistantess

Job Opportunity: Scientific Assistant at BMDS Lab

The Biomedical Data Science (BMDS) Lab is at the forefront of investigating 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 collaboration across diverse disciplines, merging expertise in medicine, biology, computer science, and data science. We are seeking a dedicated scientific assistant to join our growing team and contribute to our interdisciplinary research partnerships. The anticipated start date for this position is March 1, 2026.

About the Research Project

Traumatic spinal cord injury (SCI) profoundly impacts the lives of affected individuals and their families, leading to significant and lasting consequences. A primary challenge in predicting long-term recovery is the considerable heterogeneity in patient outcomes, which traditional clinical assessments may not fully capture. Standard neurological evaluations alone cannot adequately reflect the underlying biological and functional diversity, thereby limiting prediction accuracy and treatment strategy effectiveness. This project intends to bridge this gap by integrating neurological assessments with neurophysiological measurements and routine blood biomarkers, employing advanced machine learning techniques to synthesize these diverse data sources. By identifying the most informative clinical features, our approach aims to deliver more accurate and interpretable recovery predictions, facilitating improved patient stratification, prognosis, and personalized treatment strategies.

Responsibilities

• Explore and manage SCI datasets: Handle international databases of SCI patient data, ensuring accurate processing and integration of heterogeneous clinical, neurophysiological, and biomarker information.
• Develop advanced deep learning models: Design and implement a multi-branch neural network for integrating various 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.

Qualifications

• 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, supported by experience in statistical data analysis.
• Experience in collaborative coding practices, version control (e.g., Git), and working on computing clusters.
• Experience with SCI data or related research topics is an advantage.
• Background in biomedical projects and interdisciplinary collaboration is a plus.
• A motivation to work as part of a diverse team and a commitment to scientific excellence in your field.
• Proficiency 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.
• Advancement of your skills in data science, machine learning, and neuroinformatics through biomedical applications to critical health conditions focusing on SCI.
• Being part of a highly motivated, multidisciplinary, and collaborative team.
• Learning from experts in the field and contributing to an active research lab.

Apply online using the form below. Only applications matching the job profile will be considered. We look forward to your application!