Scientific Assistant for Biomedical Data Science - Focus on Stroke
80%, Zurich, fixed-term
The Biomedical Data Science Lab investigates data-driven solutions for healthcare applications with a focus on systemic infections and neurological conditions such as stroke. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer, and data science. We seek a motivated scientific assistant to join this growing team and contribute to interdisciplinary research partnerships. The anticipated start date is February 2025.
Project background
The Biomedical Data Science Lab at ETH Zurich invites applications for a Scientific Assistant to support our data-intensive projects in clinical research and biomedical imaging, with a particular focus on our work in stroke recovery prediction and rehabilitation. This position offers an excellent opportunity to work at the forefront of biomedical data science. One of the key projects will focus on evaluating the effectiveness of Exoskeleton Training as a complementary intervention to standard care in inpatient rehabilitation settings. This study aims to assess how the integration of exoskeleton technology alongside conventional rehabilitation methods impacts patient outcomes. Additionally, if the data and resources allow, we will attempt to develop predictive models for patient recovery. These models would aim to forecast rehabilitation outcomes based on various factors, potentially including patient characteristics, injury specifics, and response to exoskeleton training. The second key project will focus on predicting stroke recurrence, incorporating multivariate data such as patient characteristics, injury specifics, and omics data.
Job description
- Data Curation & Cleaning: Assist in the curation, cleaning, and harmonization of mainly stroke datasets.
- Data Analysis: Process and analyze data using statistical methodologies and techniques. By analyzing data from rehabilitation programs, we aim to improve prediction accuracy.
- Machine Learning Applications: Developing and refining predictive models for stroke occurance and recovery.
- Dashborad development: Collaborate on tools for omics data and dashboard visualizations.
- Scientific Software Support: Support the installation and configuration of scientific software tools (e.g., annotation tools), ensuring integration into research workflows.
- Clinical Communication: Communicate with clinical experts regarding the requirements for data preparation, feature extraction, and prediction tasks.
- Brain and Spine MRI Segmentation Harmonization, as needed: Standardize data structures, harmonize annotations, and support data preprocessing for publication potential.
Profile
- You have a Masters degree in a relevant field such as data science, computer science, physics and/or biomedical research
- You are ideally proficient in python programming with experience in statistical analysis and in the implementation of machine and deep learning models
- You have experience in software development including collaborative coding, version control and use of computer clusters
- You ideally have a background in biomedical projects with experience in interdisciplinary collaboration
- You are motivated to work as part of a team and strive towards scientific excellence in your field
- You are proficient in English in writing and speaking
Workplace
Workplace
We offer
We offer a 1-year project-based contract at the BMDS lab, 80%, that includes:
- Opportunities to engage with different communities bridging data science and biomedical research including participation in publications
- You will improve and refine your data science skills and gain insights in the biomedical background of a variety of critical health conditions, with focus on stroke
- You will be part of a highly motivated, friendly, and collaborative team
- We will support your scientific career and application for doctoral fellowships if desired
- You will be able to learn from experts and the field and be part of an active research lab
We value diversity
Curious? So are we.
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.
Further information about the BMDS lab can be found on our website.
Questions regarding the position should be directed to Liliana Paredes, by email liliana.paredes@hest.ethz.ch (no applications, please).
About ETH Zürich
Curious? So are we.
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.
Further information about the BMDS lab can be found on our website.
Questions regarding the position should be directed to Liliana Paredes, by email liliana.paredes@hest.ethz.ch (no applications, please).