Are you an ambitious researcher looking for your next challenge? Would you like to apply your expertise in theoretical physics or mathematics to a biological problem? Would you like to work with exciting multidisciplinary teams including vision scientists, experimental psychologists, instrumentation engineers, and computational modellers to understand how we process visual information?

We are seeking to appoint a Research Fellow in biological applications of theoretical physics and mathematics, funded under the UKRI ‘Building Collaboration in the Physics of Life’ scheme. The project, “A fresh look at visual sampling: (PhysFEM) How are fixational eye-movements optimised?” is in collaboration with Oxford University Department of Experimental Psychology and US collaborators. The project brings theoretical and numerical modelling (Leeds) together with advanced adaptive-optics retinal imaging, positional measurement and stimulation, and computation (Oxford) to explore the hypothesis that fixational eye-movements (FEMs) are optimised to tasks.

You will work with Prof. Daniel Read to develop analytical and numerical models of the trajectories of fixational eye movements (FEMs), exploring their influence on biological visual processing, and investigating the characteristics of FEM paths that are most optimal and useful to the observer under a range of assumptions and constraints. Working closely with the experimental team of Prof. Hannah Smithson at the University of Oxford, who measure fine-scale eye movements with an advanced Adaptive Optics Scanning Laser Ophthalmoscope (AO-SLO), you will be part of a core collaborative team, evaluating predictions from models against experiments. You will also work closely with a computational Research Fellow at Oxford and with Prof. David Brainard’s group at the University of Pennsylvania to transfer your new modelling capacity into the public domain via the ISETBio human vision modelling tool.

You will have a PhD in Physics, Mathematics, or a closely allied discipline, with a strong background in theoretical (analytical and/or numerical) modelling of physical or biological systems, and with expertise in at least one of statistical physics, information theory or Bayesian statistics. Ideally you would also have knowledge of one or more of: relevant biology, mathematical biology, biological physics, soft matter physics, vision science or image processing.

You will have the ability to conduct independent research and a developing track record of publications in international journals. In addition, you will have excellent communication, planning and team working skills with an ability to work in an interdisciplinary project.