Scientific Assistant / Scientific Assistantess

Scientific Assistant in Biomedical Machine Learning and Data Science

80%, Zurich, fixed-term

The Biomedical Data Science (BMDS) Lab is at the forefront of exploring data-driven solutions for healthcare applications, focusing primarily on neurological conditions such as spinal cord injury (SCI), lower back pain, neuro-degenerative disorders, and neurological tumors. Our research thrives on interdisciplinary collaboration, leveraging expertise across medicine, biology, and computer/data science. We are currently seeking a scientific assistant to join this dynamic team and contribute to our growing partnerships in research. The anticipated start date for this position is March 1, 2026.

Project Background

Traumatic spinal cord injury (SCI) has profound and lifelong consequences for those affected and their families. A significant challenge in predicting long-term recovery lies in the substantial heterogeneity among patient outcomes, a complexity that traditional clinical assessments often fail to capture. Standard neurological evaluations may not reflect the underlying biological and functional diversity, limiting both prediction accuracy and the effectiveness of treatment strategies. This project aims to bridge this gap by merging neurological assessments with neurophysiological measurements and routine blood biomarkers, utilizing advanced machine learning techniques to integrate these diverse data sources. By identifying the most informative clinical features, we seek to enhance recovery predictions, support better patient stratification, prognosis, and personalized treatment strategies.

Job Description

• Explore and Manage SCI Datasets: Engage with international databases housing SCI patient data, ensuring meticulous handling, preprocessing, and integration of diverse clinical, neurophysiological, and biomarker information. These datasets will be readily available at the project's inception.
• Develop Advanced Deep Learning Models: Design and implement a multi-branch neural network capable of integrating multiple data modalities into a cohesive representation.
• Implement a Multi-Task Learning Framework: Build and evaluate models that predict multiple, interrelated recovery outcomes simultaneously, exploiting 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, backed by experience in statistical data analysis.
• You have familiarity with collaborative coding practices, version control (e.g., Git), and computing clusters.
• Experience with SCI data or related research topics is advantageous.
• A background in biomedical projects and experience in interdisciplinary collaboration is a plus.
• You are motivated to work within a diverse team and are dedicated to scientific excellence in your field.
• You are proficient in both written and spoken English.

Workplace

Join a stimulating, collaborative environment at ETH Zurich, one of the world’s leading universities for science and technology.

We Offer

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

• A stimulating, collaborative environment within ETH Zurich, recognized globally for excellence in science and technology.
• The opportunity to contribute to cutting-edge biomedical data science with direct clinical relevance.
• Enhancement of your skills in data science, machine learning, and neuroinformatics through applications focused on critical health conditions, particularly SCI.
• Be part of a highly motivated and multidisciplinary team.
• Learn from experts in the field and actively contribute to a vibrant research lab.

We Value Diversity and Sustainability

At ETH Zurich, we embrace an inclusive culture that promotes equality, values diversity, and fosters a respectful environment. We are committed to ensuring that the rights and dignity of all staff and students are upheld. Visit our Equal Opportunities and Diversity website to discover how we create a fair and empowering space for everyone to thrive. Sustainability is also a core value; we are continuously striving towards a climate-neutral future.

Curious? So Are We.

We invite you to apply online using the form below. Please ensure your application includes the following documents:

• Curriculum Vitae (CV): Detailing your educational background, previous positions, and any relevant publications.
• Task-based Statement (Maximum 1 page): Briefly outline your approach for integrating longitudinal multi-assessment data to predict recovery after SCI. Include strategies to combine various clinical assessments (demographic, neurological, neurophysiological, and biomarker data) and discuss methodologies to effectively utilize all available data, taking into account repeated measurements and missing assessments.
• Contact Information for Two References

Please note that only applications matching the job profile will be considered.

For inquiries regarding the position, please contact Dr. Olga Taran via email at olga.taran@hest.ethz.ch (no applications).

About ETH Zurich

ETH Zurich is a world-renowned university specializing in science and technology. Our institution is recognized for its exceptional education, innovative fundamental research, and the effective transfer of new knowledge into society. With over 30,000 individuals from more than 120 countries, ETH Zurich promotes independent thinking in an environment that inspires excellence. Located in the heart of Europe, we collaborate globally to tackle the challenges of today and tomorrow.