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Computational modelling of the PI3K/mTOR signalling network to discover novel cancer therapies

Description 
The PI3K-Akt-mTOR signalling network plays a pivotal role in the regulation of cell growth and proliferation, and is highly complex with multiple feedback loops, pathway crosstalk, upstream regulators and downstream functions. Its frequent aberrations in cancers makes this network an important therapeutic target, and indeed many targeted drugs have been developed directed at its components. However, the clinical success in inhibiting PI3K, Akt, mTORC1 and/or mTORC2 has been disappointing due to the emergence of drug resistance. This project will employ an innovative and integrative approach that combines computational network modelling with cutting-edge experimentation to gain a systems-level understanding of the network dynamics in cancer cells before and after drug treatment. This knowledge together with model simulations will help design new therapeutic strategies that exploit network vulnerabilities and are capable of overcoming resistance. Predictions will then be tested experimentally in the wet lab. Our lab has both dry- and wet-lab capacities that enable the iterative cycles of model refinement and experimental validation integral to this systems approach. Students will work in a highly stimulating and interdisciplinary research environment consisting of both computational and experimental scientists. Students with either excellent computational (physics, maths, engineering, etc.) or experimental background (or both) are encouraged to apply.
Essential criteria: 
Minimum entry requirements can be found here: https://www.monash.edu/admissions/entry-requirements/minimum
Keywords 
PI3K-Akt-mTOR signalling, mathematical modelling, targeted therapy, cell signalling, systems biology, Department of Biochemistry & Molecular Biology
Available options 
PhD/Doctorate
Masters by research
Honours
Short projects
Time commitment 
Full-time
Top-up scholarship funding available 
No
Physical location 
Clayton Campus

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