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. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer 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 July 1, 2025.

Traumatic SCI has profound and lifelong implications for affected patients and their families. A major challenge in drug development for traumatic SCI is the high failure rate of clinical trials despite promising preclinical evidence. One of the key obstacles is the assumption that SCI can be treated without accounting for substantial variability in individual biological, clinical, health, and injury-related characteristics. Traditionally, a uniform physiological recovery capacity and consistent benefits from experimental treatments are assumed, contradicting the established understanding of natural recovery variability. The proposed project aims to bridge this critical gap by distinguishing between patients’ baseline natural recovery and treatment-induced improvements. By isolating the true treatment effect, the project seeks to provide a clearer and more accurate assessment of how interventions influence recovery trajectories.

The scientific assistant will:

• Familiarize themselves with the various international databases collecting data on SCI patients. These data are readily available at the start of this project.
• Implement, train, and benchmark state-of-the-art data science pipelines to characterize SCI recovery trajectories and injury patterns. Integrate personalized physiological measurements into a recovery prediction model, while adapting Bayesian Neural Networks for SCI data and analyzing the impact on model uncertainty.
• Develop and implement methods to utilize predicted natural recovery to effectively isolate, analyze, and quantify treatment-induced improvements in SCI patients.
• Develop an exploratory web platform for traumatic SCI recovery. Collaborate with clinical experts to gather and define requirements, ensuring the platform aligns with the needs of both patients and healthcare professionals.

• You hold a Master's degree in a relevant field such as data science, computer science, physics, computational biology, or biomedical research.
• You are proficient in Python programming, with experience in statistical analysis and implementing machine and deep learning models using Keras/TensorFlow and/or PyTorch.
• You have experience in collaborative coding, version control, and utilizing computer clusters.
• Ideally, you have a background in biomedical projects and experience in interdisciplinary collaboration. 
• Experience in SCI-related research 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.

We offer a 1-year project-based contract at the BMDS Lab (80–100% workload), with the potential for a second-year extension. The position includes:

• Opportunities to engage with diverse communities bridging data science and SCI research, leading to high-impact publications.
• Enhance your data science skills while gaining insights into the biomedical aspects of critical health conditions, with a focus on SCI.
• Be part of a highly motivated, multidisciplinary, and collaborative team.
• Learn from experts in the field and contribute to an active research lab.
• We will support your scientific career development and application for doctoral fellowships, if desired.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

We look forward to receiving your online application with the following documents:

• CV indicating your educational background, previous positions and optional publications
• A 1-page letter outlining your motivation to join the BMDS lab and the particular project

Please note that we exclusively accept applications submitted through our online application portal.  Applications via email or postal services will not be considered. Applications will be reviewed on a rolling basis.

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

Questions regarding the position should be directed to Olga Taran, by email [email protected] (no applications).

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.