Research Associate in Mathematical Biology (University of New South Wales Institute for Infection and Immunity in Society)

Research Associate / Post-Doctoral Fellow in Mathematical Biology Apply now Job no: 499735 Work type: Full-time Location: Sydney, NSW Categories: Post doctoral research fellow The Kirby Institute for Infection and Immunity in Society UNSW Medicine Ref 499735 Opportunity to work on SIV / HIV infection dynamics Create and analyse mathematical models (Level A or B) $96K-$126K plus 17% superannuation and leave loading (pro-rata if part time) Fixed term 3 years, full time or part time This post-doctoral position is based at the Kirby Institute in UNSW, which is a leading global research institute dedicated to the prevention and treatment of infectious diseases. This work sits within The Infection Analytics Program (IAP) which uses mathematical and computational approaches to better understand immunity to major infectious disease threats such as HIV and malaria. The successful candidate will develop and use mathematical models to interpret experimental and clinical data to help understand the dynamics of host-viral interactions in HIV infection (animal and human). To succeed in this position you will develop familiarity with the HIV literature and the underlying biology, be able to analyse experimental data using biostatistical analysis, ODE and stochastic modelling and be able to use hypothesis testing to address the underlying mechanisms of infection and immunity. This is an interdisciplinary field that applies techniques of computer science, applied mathematics, and statistics to address biological problems, hence you will not only have skills to create and analyse mathematical models but at the same time understand the models from a scientific perspective. You must systematically address each of the following skills in the cover letter of your application. Applications that do not address these skills will not be considered. Reference to specific examples highlighting your skills is strongly encouraged. PhD, in mathematics / physics / statistics or other quantitative discipline Demonstrated ability to model experimental data using one or more of Biostatistical analysis methods ODE or PDE modelling Stochastic modelling Computer modelling Interest in modelling in immunology and infection dynamics. Experience in critically analysing and reporting on an existing scenario using relevant real world data combined with mathematical, statistical or computer models. Creativity in your approach to solving scientific questions. Ability to describe the impact and significance of your scientific findings to a non-technical audience. Success in funding applications, student supervision and superior publication output required for appointment at the higher levels You should systematically address all the selection criteria in your application. Please also provide a copy of your undergraduate transcript where available. PD-Research Associate_Post-Doctoral Fellow.pdf Contact: Professor Miles Davenport, Program Head IAP E: m.davenport@unsw.edu.au T: 02 9385 2762 Applications close: 21^th August 2020 Position Description Advertised: 23 Jul 2020 AUS Eastern Standard Time Applications close: 21 Aug 2020 AUS Eastern Standard Time If you apply for this position please say you saw it on Bioloxy

Research Associate / Post-Doctoral Fellow in Mathematical Biology

Apply now Job no: 499735

Work type: Full-time

Location: Sydney, NSW

Categories: Post doctoral research fellow

The Kirby Institute for Infection and Immunity in Society

UNSW Medicine

Ref 499735

Opportunity to work on SIV / HIV infection dynamics
Create and analyse mathematical models
(Level A or B) $96K-$126K plus 17% superannuation and leave loading (pro-rata if part time)
Fixed term 3 years, full time or part time

This post-doctoral position is based at the Kirby Institute in UNSW, which is a leading global research institute dedicated to the prevention and treatment of infectious diseases. This work sits within The Infection Analytics Program (IAP) which uses mathematical and computational approaches to better understand immunity to major infectious disease threats such as HIV and malaria.

The successful candidate will develop and use mathematical models to interpret experimental and clinical data to help understand the dynamics of host-viral interactions in HIV infection (animal and human). To succeed in this position you will develop familiarity with the HIV literature and the underlying biology, be able to analyse experimental data using biostatistical analysis, ODE and stochastic modelling and be able to use hypothesis testing to address the underlying mechanisms of infection and immunity.

This is an interdisciplinary field that applies techniques of computer science, applied mathematics, and statistics to address biological problems, hence you will not only have skills to create and analyse mathematical models but at the same time understand the models from a scientific perspective.

You must systematically address each of the following skills in the cover letter of your application. Applications that do not address these skills will not be considered. Reference to specific examples highlighting your skills is strongly encouraged.

PhD, in mathematics / physics / statistics or other quantitative discipline
Demonstrated ability to model experimental data using one or more of

Biostatistical analysis methods
ODE or PDE modelling
Stochastic modelling
Computer modelling

Interest in modelling in immunology and infection dynamics.
Experience in critically analysing and reporting on an existing scenario using relevant real world data combined with mathematical, statistical or computer models.
Creativity in your approach to solving scientific questions.
Ability to describe the impact and significance of your scientific findings to a non-technical audience.
Success in funding applications, student supervision and superior publication output required for appointment at the higher levels

You should systematically address all the selection criteria in your application. Please also provide a copy of your undergraduate transcript where available.

Download File PD-Research Associate_Post-Doctoral Fellow.pdf