New mathematical models to make biology predictable

ScholarLink Inc.; Brisbane; Remote; AUD 32,000 - 39,000; Full time

Job summary

Queensland University of Technology in Australia invites applications for a PhD student in applied mathematics within the MACSYS node. The project focuses on mathematical and computational modelling of biological data, including multi-omic fingerprints and reaction-diffusion frameworks.

The successful candidate will have strong modelling training and programming skills (Julia, Python, C++), be eligible for a PhD at QUT, and join a large group of researchers in the MACSYS ecosystem.

Qualifications

• Strong training in mathematical modelling and numerical methods.
• Eligibility to enrol in a PhD at Queensland University of Technology.
• Excellent programming skills in Julia, Python and C++ are essential.

Responsibilities

• Develop and deploy mathematical/computational models for MACSYS.
• Quantify multi-omic data and model cellular responses to stress.
• Collaborate with researchers in the School of Mathematical Sciences.

Skills

Julia

Python

C++

Mathematical modelling

PDEs

Strong communication

Education

First-class Honours degree

Research Master's degree

Tools

NumPy

PDE Solvers

Job description

# New mathematical models to make biology predictablePh.D·Queensland University of Technology·School of Mathematical Sciences·AustraliaFunding: 35000 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 (https://www.qut.edu.au/courses/doctor-of-philosophy). A tax-free scholarship of approximately AU$35000pa for full-time students will support living costs for up to 3 years. Submit your application by email to [e-mail]. 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 [e-mail]. Applications accepted all year round. Funded PhD Project (Students Worldwide).