Post Doctoral Research Associate - Mathematical Modelling

University of York; York; On-site; GBP 40,000 - 55,000; Full time

Job summary

A leading university in the UK is seeking an experienced mathematical modeller to develop advanced genetics-based methods for controlling mosquito-borne diseases. The role involves analyzing genetic control systems and integrating empirical data from laboratory research. Applicants should have a PhD in mathematics or a related field, along with strong skills in mathematical modelling and research writing. This position offers a collaborative environment with opportunities for impactful research.

Qualifications

• PhD in a relevant subject (mathematics or mathematically-oriented biological science), or equivalent.
• Knowledge of mathematical modelling to engage in high-quality research.
• Good communication skills, ability to write up research work for publication in high profile journals.
• Prior knowledge of population genetics/dynamics would be desirable, but not essential.

Responsibilities

• Analyse potential genetic control systems from concept models to sensitivity analysis.
• Integrate empirical data from developed systems.
• Develop appropriate modelling frameworks independently.

Skills

Mathematical modelling

Research writing

Good communication skills

Knowledge of population genetics/dynamics

Education

PhD in relevant subject

Job description

Department

We are seeking an experienced mathematical modeller. Our group is developing a range of advanced genetics-based methods for controlling mosquito-borne diseases, based on engineering novel heritable traits in the mosquito. Mathematical modelling informs every step of development, from testing new ideas for utility and sensitivity to various deviations from 'ideal' implementation, through to experimental plans and analysis of actual data (laboratory and potentially field) regarding prototype strains embodying these concepts.

The successful candidate will help develop theoretical understanding of theoretical (conceptual) and actual (empirical implementations) of a range of potential genetic control systems, informing and informed by empirical (wet-lab) development. We, our collaborators, and others in the field have used a range of methods for deterministic and stochastic models, e.g. difference and differential equations, including time-delay differential equations, recursion equations. See, for example, papers by Alphey and either Mike Bonsall or Matt Edgington, or those from Jackson Champer, Austin Burt or John Marshall groups. Several frameworks have been developed that can be very helpful within their capabilities, e.g. SLiM and MGDrive. A key element of the role is to select appropriate methods to address the questions in hand.

Nominal start date is Jan 2026 but potentially negotiable in either direction.

Role

The core of the role is to analyse all aspects of potential genetic control systems, from simple “concept” models for new ideas, to sensitivity analysis for imperfections (undesirable but likely unavoidable aspects such as fitness cost, imperfect performance of system components), considerations of fitness, resistance, spatial issues etc. An important element is to integrate empirical data from such systems as they are developed.

The group is primarily wet-lab/empirical, so there is plenty of support for providing questions and helping interpret answers, less so for technical questions regarding modelling approaches. However we have interested mathematicians in both the Dept of Biology and Dept of Mathematics, as well as external collaborators. Nonetheless, the ability to self-motivate and self-direct the development of appropriate modelling frameworks is a key element of the role.

Skills, Experience & Qualification needed

• PhD in a relevant subject (mathematics or mathematically-oriented biological science), or equivalent
• Knowledge of mathematical modelling to engage in high-quality research.
• Good communication skills, ability to write up research work for publication in high profile journals
• Prior knowledge of population genetics/dynamics would be desirable, but not essential

Interview date: To be confirmed

For informal enquiries: please contact Prof Luke Alphey [e-mail]