Development of a highly innovative label-free & deep-learning based analysis method: Histoplasmonic Tissue Cytometry

The doctoral candidate (DC) will perform applied research in bioinformatics, i.e., the extraction of numerical values from biological samples, by engaging deep learning technologies to microscopic images with the aim to develop a novel solution for future clinical diagnostics of cancer.

To develop algorithms that allow to extract diagnostic and prognostic information from label-free images of tumour samples on specific nanoparticle coated slides:

• The DC will develop experimental algorithms using deep-learning technologies for analysis of human and/or mouse cancer tissue.
• The DC will develop and execute a test plan comparing to visual analysis results provided by human experts (pathologists).
• The DC will develop a Graphical User Interface (GUI) that allows to run the algorithm either in a test environment (demonstrator implementation) and/or the commercial image analysis platforms provided by the hosting institution (TissueGnostics).
• The DC will document his/her work in a Quality Management and ISO 13485-compliant way (training and instructions to be provided by the hosting institution).

Principal techniques employed in this project: microscopy, image analysis and object segmentation, spectral unmixing, machine & deep learning solutions.

This project is part of the doctoral network (DN) “eRaDicate”, an international, multidisciplinary, and intersectoral cancer drug research and development programme. The network combines training and research in almost equal parts. Its aim is to empower 11 young scientists to become specialists in cancer research and drug development, while developing new therapies against cancer stem cell-driven relapse and metastasis.

The DN eRaDicate is built around a community of leading researchers and all Doctoral Candidates (DC) will be part of this community through secondments, training schools, eRaDicate events, and conferences. The research will be performed at 7 universities (Medical University of Vienna, University of Wroclaw, Medical University of Warsaw, University of Warsaw, University of Birmingham, University of the Negev, and Trinity College Dublin) and a company (TissueGnostics GmbH). The DCs will be employed by the host institution of the selected project and enrolled in the host organisation’s or affiliated university’s PhD programme.

The objective of the network is to understand the role of nuclear receptors, such as retinoic acid receptor (RAR) and vitamin D receptor (VDR), in cancer development and to design and synthesise highly innovative compounds targeting these receptors, to become therapies against cancer stem cell-driven relapse and metastasis. Furthermore, the DCs in the network will devise pre-formulation strategies for the compounds and develop a novel, deep learning-based cancer analysis and diagnostics method.

Specific requirements:

• Master degree in Bioinformatics, Computer Science or a related subject.
• Experience with biomedical image analysis and data visualization.
• Knowledge of the programming language Python; optionally also other languages like JULIA or R.
• Proficiency in written and spoken English.
• Applicants must fulfil the requirements of the recruiting institutions.
• The applicant must be eligible to enrol in a PhD programme at the Medical University of Vienna.

To apply go to: https://www.eradicate-project.eu/recruitment/.