Post-doctoral researcher / Visiting scientist
Computational Pathology: Histopathology image analysis
Project description: Histopathology image analysis
In digital pathology, we focus on the analysis of digitized histopathology and molecular expression images as well as cytology images. Imaging of tissue specimens is a powerful tool to extract quantitative metrics of phenotypic properties while preserving the morphology and spatial relationship of the tissue microenvironment. Staining technologies such as immunohistochemistry (IHC) and in situ hybridization (ISH) further empower the evidencing of molecular expression patterns by multicolor visualization. Such techniques are thus commonly used for predicting disease susceptibility and stratification and treatment selection and monitoring. However, the process of translating molecular expression imaging into direct health benefits has been slow.
Two major factors contribute to that. On the one hand, disease susceptibility and progression is a complex, multifactorial molecular process. Diseases such as cancer exhibit tissue and cell heterogeneity, impeding the differentiation between different stages or types of cell formations, most prominently between inflammatory response and malignant cell transition. On the other hand, the relative quantification of the stained tissue selected features is ambiguous, tedious and thus time-consuming and prone to clerical error, leading to intra- and interobserver variability and low throughput. At IBM Research – Zurich, we are developing advanced image analytics to address both limitations, aiming to transform the analysis of stained tissue images into a high-throughput, robust, quantitative and data-driven yet explainable science.
For our growth area in digital pathology we are looking for motivated candidates for the enhancement and advancement of our computational framework.
- PhD in Computer Science, Computer Vision, or a related field
- Strong programming skills in C/C++ and Python
- Strong theoretical understanding of classical computer vision techniques and machine-learning architectures
- Practical experience with deep-learning frameworks
- Experience with continuous integration frameworks and adherence to coding standards
- Proven track record of conducting independent research
- Excellent communication and teamwork skills
In addition, a background in either histopathology, biology, bioinformatics or healthcare sciences could be beneficial.
IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.
How to apply
If you are interested, please send your application to Dr. Maria Gabrani (firstname.lastname@example.org).