The proposed research concerns modeling of tumor growth within specific organs. In this process, cancer cells are initially constrained in a restricted environment then the growing mass tends to molten and spread as nutrients and growing factors are slowly released in the surrounding cancer environment. One of the main objectives of this project is to design numerical models that could provide an accurate description of the evolution of the liquid-solid growing interface of the early stages of cancer growth, so as to gain understanding of how one could predict malignant progression of pre-cancer lesions. In particular, an approach based on phase field approximations of the cancer invasive front will be developed. Description of cancer growing mass at different stages will be derived by image analysis of diagnostic data (e.g. ultrasound imaging and Nuclear Magnetic Resonance). From the numerical point of view, such representation of the growing front should allow a more robust modeling of malignant progression, while also providing insight on the relevant relationships between early lesions shape and macroscopic cancer development. The final goal is to develop a computer-assisted diagnostics (CAD) tool to improve early cancer detection.
CONTEXT
The BioComputing UP Laboratory, led by Prof. Silvio Tosatto, is a dynamic group of about fifteen people working on several aspects of prediction of protein structure & function employing techniques at the intersection between biology, medicine, chemistry, physics & computer science. Our aim is to integrate the development of novel methods and their application to biologically relevant problems. The group is currently funded by the Italian Association for Cancer Research (AIRC) and the European infrastructure for bioinformatics (ELIXIR). In addition, we are also coordinating the Marie Curie RISE consortia IDPfun and REFRACT
Required education: level Master degree in either Bioinformatics, Informatics, Physics, Mathematics, Engineering, Bioscience engineering, or an equivalent degree.
- Candidates should comply with the following requirements:
- Be highly motivated to work on interdisciplinary research.
- Have a knowledge of computer science and/or machine learning and/or statistical/mathematical modeling and/or bioinformatics.
- Have an interest in biology or molecular biology.
- Be proficient in programming languages such as Python, R and/or C++ as well as Linux systems.
- Show fluency in spoken and written English
- Have a knowledge of mathematics techniques for solid/liquid interface modeling evolution using phase field paradigms.
To apply, please send your CV and a motivation letter and brief description of your research background as well as the names of two (or more) references to: biocomp@bio.unipd.it.