Imperial College London is a science-based institution with the greatest concentration of high-impact research of any major UK university. The Department of Bioengineering at Imperial College London is leading the bioengineering agenda both nationally and internationally, advancing the frontiers of our knowledge in the discipline’s three main areas:

Biomedical Engineering: Developing devices, techniques and interventions for human health. Biological Engineering: Solving problems related to the life sciences and their applications for health. Biomimetics: Using the structures and functions of living organisms as models for the design and engineering of materials and machines.

Research topic: Learning and memory are among the most fascinating topic of neuroscience, yet our understanding of it is only at the beginning. Learning is thought to change the connections between the neurons in the brain, a process called synaptic plasticity. Using mathematical and computational tools, it is possible to model synaptic plasticity across different time scales, which helps understand how different types of memory are formed. The Postdoc candidate will be designing plastic artificial neural networks which are modelling the hippocampal complex.

Requirements: The Computational Neuroscience Laboratory, headed by Dr. Clopath, is looking for a talented Postdoc, working in the field of computational neuroscience. The perfect candidate has a strong mathematical, physical or engineering background, and has done a PhD in the field of computational neuroscience. The ideal candidate has expertise modelling learning at the biophysical level for example looking at trafficking involved in plasticity, they should have a background in data analysis and a plus would be using deep learning tools for neuroscience data, finally they should be exposed to circuit modelling.

Requirements: The Computational Neuroscience Laboratory, headed by Dr. Clopath, is looking for a talented Postdoc, working in the field of computational neuroscience. The perfect candidate has a strong mathematical, physical or engineering background, and has done a PhD in the field of computational neuroscience. The ideal candidate has expertise modelling learning at the biophysical level for example looking at trafficking involved in plasticity, they should have a background in data analysis and a plus would be using deep learning tools for neuroscience data, finally they should be exposed to circuit modelling.

You must have a good undergraduate degree/ MSc in physics, mathematics, engineering (or equivalent) and a PhD in computational neuroscience (or equivalent). You will have previous experience in computational neuroscience.

The opportunity to continue your career at a world-leading institution sector-leading salary and remuneration package (including 38 days off a year)