New Mathematical Models To Make Biology Predictable (Brisbane)

New Mathematical Models To Make Biology Predictable (Brisbane)

02 Nov
|
Qut Centre For Robotics
|
Brisbane

02 Nov

Qut Centre For Robotics

Brisbane

# New mathematical models to make biology predictablePh.D·Queensland University of Technology·School of Mathematical Sciences·AustraliaFunding: ***** AUD per yearPosition type: StudentshipLevel: Ph.DLanguage: English## About the PositionWe seek a PhD student in applied mathematics to join the Queensland University of Technology node of MACSYS.
MACSYS is the Australian Research Council Centre of Excellence for the Mathematical Analysis of Cellular Systems.
The PhD student will work with QUT researchers in the development and deployment of mathematical and computational models that describe experimental data generated within the MACSYS ecosystem.
Examples of specific biological applications include building tools to understand and quantify multi-omic data that acts as a fingerprint of cellular responses to external stresses; cyanobacterial CO2 concentrating mechanisms via reaction-diffusion modelling frameworks, understanding/predicting outcomes of microbial competition during industrial fermentation processes; and using mathematical models to design and optimize protein switch technology.
The successful applicant will be based in the School of Mathematical Sciences at QUT.
The applicant will join a large group of other PhD candidates and research fellows within the MACSYS ecosystem who are all working on related projects in mathematical biology.




The successful candidate will have appropriate training in mathematical modelling (e.g. via training in applied mathematics, engineering, computer science or related discipline) and will already have well-developed skills in programming.
Applicants should hold a first class Honours degree or equivalent (e.g. a research Master's degree) in physics, mathematics, engineering or computer science.
Strong academic performance, excellent written communication skills, and expertise in computational techniques (Julia, Python, C++) are essential.
Training in implementing numerical methods for solving partial differential equations is essential.
The applicant must be eligible to enrol in a PhD at Queensland University of Technology ().
A tax-free scholarship of approximately AU$*****pa for full time students will support living costs for up to 3 years.
Submit your application by email to ******.
Your application will include a cover letter (maximum 2 pages), an up-to-date CV indicating education, prior research experience and skills, full academic transcripts, and contact details and email addresses of two referees.
For further information please contact Professor Matthew Simpson at ******.
Applications accepted all year round.
Funded PhD Project (Students Worldwide).
#J-*****-Ljbffr

📌 New Mathematical Models To Make Biology Predictable (Brisbane)
🏢 Qut Centre For Robotics
📍 Brisbane

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