Scientific Assistant / Scientific Assistantess

Scientific Assistant in Biomedical Machine Learning and Data Science

80%, Zurich, fixed-term

The Biomedical Data Science (BMDS) Lab investigates data-driven solutions for healthcare applications with a focus on neurological conditions such as spinal cord injury (SCI), lower back pain, neuro-degenerative disorders, and neurological tumors. Our research thrives on the collaboration across disciplines, integrating expertise in medicine, biology, computer science, and data science. We are seeking a scientific assistant to join this growing team and contribute to interdisciplinary research partnerships. The anticipated start date is March 1, 2026.

Project Background

Traumatic spinal cord injury (SCI) significantly affects individuals and their families, presenting lifelong challenges. One major hurdle in forecasting long-term recovery is the considerable variability in patient outcomes that traditional clinical assessments may not fully capture. Standard neurological evaluations alone are unable to reflect the underlying biological and functional diversity, which limits both prediction accuracy and treatment effectiveness. This project aims to bridge this gap by integrating neurological assessments with neurophysiological measurements and routine blood biomarkers, utilizing advanced machine learning techniques to combine these diverse data sources. Our approach seeks to identify the most informative clinical features, ultimately providing more accurate and interpretable recovery predictions, enhancing patient stratification, prognosis, and personalized treatment strategies.

Job Description

• 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 are readily available at the start of the project.
• Develop advanced deep learning models: Design and implement a multi-branch neural network capable of integrating multiple 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, interpretability, and generalization.

Profile

• You hold a Master's degree in Computer Science, Data Science, Biomedical Engineering, or a related field.
• You possess strong Python programming skills and 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.
• You are familiar with collaborative coding practices, version control (e.g., Git), and working on computing clusters.
• Experience with SCI data or related research topics is an advantage.
• A background in biomedical projects and experience in interdisciplinary collaboration is a plus.
• You are motivated to work as part of a diverse team and are committed to scientific excellence in your field.
• You are proficient in both written and spoken English.

Workplace

Located in a cutting-edge research environment, you will work alongside experts dedicated to advancing the field of biomedical data science at ETH Zurich.

We Offer

We provide a 1-year project-based contract at the BMDS Lab (80% workload).

• A stimulating, collaborative environment within ETH Zurich, a leading university in 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 applied to critical health conditions, with a focus on SCI.
• Membership in a highly motivated, multidisciplinary, and collaborative team.
• Opportunities to learn from experts in the field and actively contribute to an impactful research lab.

We Value Diversity and Sustainability

In line with our values, ETH Zurich promotes an inclusive culture. We encourage equality of opportunity, value diversity, and nurture a working and learning environment that respects the rights and dignity of all staff and students. Visit our Equal Opportunities and Diversity website to discover how we cultivate a fair and open environment that enables everyone to thrive. Sustainability is a core value for us, and we are consistently striving towards a climate-neutral future.

Curious? So Are We.

Apply online using the form below.

• Curriculum Vitae (CV): outlining your educational background, previous positions, and publications (if applicable).
• Task-based statement (maximum 1 page): Briefly describe how you would approach the integration of longitudinal multi-assessment data for recovery prediction after SCI, suggesting strategies to combine longitudinal clinical assessments (demographic, neurological, neurophysiological, and biomarker data) to predict recovery outcomes, and discussing methodological approaches to effectively utilize all available data, accounting for repeated measurements and missing assessments.
• Contact information from two references.

Please note that only applications matching the job profile will be considered. For inquiries regarding the position, please reach out to Dr. Olga Taran at olga.taran@hest.ethz.ch (no applications).

About ETH Zurich

ETH Zurich is a leading university globally known for its specialization in science and technology. We are renowned for our excellent education, cutting-edge fundamental research, and direct transfer of new knowledge into society. With over 30,000 individuals from more than 120 countries, we promote independent thinking and foster an environment that inspires excellence. Centrally located in Europe, we are committed to solving the global challenges of today and tomorrow.