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Computational Neuroscience Research Associate
2 months ago
Embark on a Fulfilling Career Journey.
Innovating through Research.
Research Associate in Computational Neuroscience
Grade G(£31, - £36, p.a. pro rata)
36-month full-time fixed-term contract
Position Overview
We invite applications for the position to collaborate with esteemed researchers on a project funded by the Leverhulme Trust, focusing on the intricate relationship between brain morphology and its functional implications.
The project aims to create innovative computational tools designed to effectively address neural field models on complex geometries. This research will enhance our understanding of how spatial variations in the cortex influence brain functionality. By utilizing advanced computational engineering techniques, we will accurately model brain activity on complex cortical structures and investigate how morphological changes in the brain impact brainwave characteristics across different species and evolutionary contexts.
Applicants should possess a PhD or equivalent in a relevant discipline such as mathematics, engineering, or computer science. A solid foundation in computational mathematical modeling is crucial. Additionally, familiarity with one or more of the following areas is highly advantageous: numerical solutions of partial integro-differential equations, isogeometric analysis, numerical bifurcation analysis, and computational geometry.
Candidates are expected to demonstrate confidence, organizational skills, effective communication abilities, and a collaborative spirit, while also being capable of independent work. The successful candidate will contribute to scientific publications, present findings at relevant conferences, and undertake regular collaborations with partner institutions, including an extended visit during the latter part of the project. Evidence of prior research outputs that reflect the candidate's experience level is essential.
For further information, please refer to the role profile. We encourage applications from individuals who may not meet every requirement, as we value diverse experiences and perspectives.
