We are looking for an experienced researcher whose expertise lies in mechanistic cardiac electrophysiology modelling, to work with Prof. Gary Mirams and Prof. Simon Preston on an externally-funded project entitled “A continually-learning framework for uncertainty quantification and translation of preclinical studies to human cardiovascular safety”. The aim of the project is to develop a statistical decision-support tool that quantifies the accuracy of mechanistic electrophysiology model predictions for drug-induced changes to electrophysiology observed in animal cardiovascular safety studies.

We believe that our talented and inclusive teams deliver the highest quality research and are seeking applications from quality candidates who enhance the diversity of our existing team. The School is committed to creating opportunities for people traditionally under- represented in Mathematical Sciences and strives to maintain an environment where people can be their authentic selves.

You will be able to carry out research of a high standard, and evidence, through your experience, how you will undertake original research of international excellence. It will be key that you prepare you work for publication in leading journals, and contribute to its distribution at national and international meetings.

You will be an organised researcher who can evidence:

• A PhD, or equivalent, in mathematics or a relevant branch of mathematics, physics, bioengineering or a closely related discipline.
• Excellent communication and organisational skills.
• The ability to work independently and as part of a multidisciplinary and multicultural team.
• Ability to devise, advise on and manage a research programme.
• A consistent track record of high-quality peer reviewed publications in cardiac electrophysiology modelling.

This full-time position (36.25 weekly hours) is available from 1st July 2026 [or as soon as possible thereafter] until 31st March 27. Many of our team have flexible working patterns so we’re open to discuss flexible working arrangements with you.

We are looking for an experienced researcher whose expertise lies in mechanistic cardiac electrophysiology modelling, to work with Prof. Gary Mirams and Prof. Simon Preston on an externally-funded project entitled “A continually-learning framework for uncertainty quantification and translation of preclinical studies to human cardiovascular safety”. The aim of the project is to develop a statistical decision-support tool that quantifies the accuracy of mechanistic electrophysiology model predictions for drug-induced changes to electrophysiology observed in animal cardiovascular safety studies.

We believe that our talented and inclusive teams deliver the highest quality research and are seeking applications from quality candidates who enhance the diversity of our existing team. The School is committed to creating opportunities for people traditionally under- represented in Mathematical Sciences and strives to maintain an environment where people can be their authentic selves.

You will be able to carry out research of a high standard, and evidence, through your experience, how you will undertake original research of international excellence. It will be key that you prepare you work for publication in leading journals, and contribute to its distribution at national and international meetings.

You will be an organised researcher who can evidence:

• A PhD, or equivalent, in mathematics or a relevant branch of mathematics, physics, bioengineering or a closely related discipline.
• Excellent communication and organisational skills.
• The ability to work independently and as part of a multidisciplinary and multicultural team.
• Ability to devise, advise on and manage a research programme.
• A consistent track record of high-quality peer reviewed publications in cardiac electrophysiology modelling.

This full-time position (36.25 weekly hours) is available from 1st July 2026 [or as soon as possible thereafter] until 31st March 27. Many of our team have flexible working patterns so we’re open to discuss flexible working arrangements with you.