Machine learning and imaging-based feedback for ‘smart’ cancer organoids culture automation
We are looking for a student to join our interdisciplinary team to develop ‘smart’ imaging algorithms, implemented in Python, as a key-step towards the automated handling and the biobanking of patient-derived cancer organoid cultures.
Patient-specific cancer organoid models hold great promise for the advancement of precision oncology. However, the currently employed manual organoid culturing techniques are cumbersome, tedious, and extremely time-consuming, thus greatly restricting the use, and further scale-up of patient-derived organoid cultures for large-scale drug screening towards personalized medicine applications.
Seeking to realize the immense potential of patient-specific organoids, and paving the way towards patient-centred diagnostics and therapy, we aim to establish capabilities for the automated handling and expansion of cancer organoid cultures.
Developing the ability to culture organoids in a fully automated manner, and, critically, under defined and highly reproducible conditions, requires identification of, and ‘smart’ feedback on critical features and parameters, such as organoid morphology, or culture density, in order to maintain long-term viability, and to obtain robust and homogenous experimental models.
In this cutting-edge project, you will develop metrics and algorithms for computational image analysis and machine learning, to provide ‘intelligent input’ to our robotic platform, as a key contribution towards implementing fully automated organoid culture handling.
Required skills :
- Computer programming (Python)
- Image analysis
- English required; basic knowledge of French appreciated
When : February to September (2023)
Where : BET Bioengineering & Organoids Technology platform
in AGORA Cancer Research Center close to CHUV in Lausanne.
This Master project will be co-supervised by EPFL Center for Imaging executive director Dr. Laurène Donati & principal scientist Dr. Edward Andò.
To send your application or for more information, you can contact by email the Automation specialist of our platform, Dr. Julia Tischler : [email protected]