Master’s student position

Computational Pathology: Histopathology image analysis

Ref. 2019-18

Project description: Histopathology image analysis

Computational PathologyIn 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.

Requirements

  • Studying Computer Science, Electrical Engineering or a related field
  • Working knowledge of Python, or equivalent
  • Working knowledge of deep-learning architectures and image processing
  • Comfortable knowledge of machine learning

Diversity

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 (mga@zurich.ibm.com).