About the Project
"3D Computational modelling and simulation of CaMKII dynamics in neurons" to be delivered by the University of Edinburgh [Supervisors: Dr. Melanie Stefan (Centre for Discovery Brain Science, University of Edinburgh), Dr David Sterratt (School of Informatics, University of Edinburgh) and Dr Roman Bauer (School of Computing, Newcastle University)] and CERN openlab (https://home.cern/science/computing/cern-openlab) [EPO supervisor: Dr Fons Rademakers].
Learning relies on activity-dependent changes in synaptic strength. In many neurons, the post-synaptic terminal is housed in a specialised subcellular compartment, the dendritic spine. The spine undergoes a number of changes when neuronal connections are strengthened. Some of those changes are biochemical, with several signalling cascades interacting with each other and inducing changes to local protein activity as well as, on a longer scale, production of new proteins. Other changes are related to spatial arrangement: Some molecules are transported to other locations, some assemble into larger structures. Along with that, the dendritic spine grows in size. The changes in biochemistry and spine structure are not independent, but instead influence each other.
We want to build computational models that represents both the biochemical and the structural events that happen when we learn. Modelling both biochemical reaction pathways and changes in the shape and size of cellular compartment is currently an open challenge. We propose to generate a “dynamic shape modelling pipeline” that combines the 3D modelling capabilities of BioDynaMo and the stochastic biochemical reaction modelling of MCell. This pipeline be a set of scripts that that allow a model to run in parallel both in Mcell and in BioDynaMo, with information being exchanged every few time steps, so that changes in biochemical activity can inform changes in compartment size and vice versa. This tool will allow us to look at the interplay of chemical regulation, location, and 3D environment of signalling molecules.
With this dynamic shape modelling pipeline in place, you will construct an “in-silico dendritic spine”, which for the first time allows us to address the question of how biochemical processes and changes in 3D spine structure influence each other. Versions of the model can be used to represent both healthy individuals and neurological diseases with known dendritic spine phenotypes.
Enquiries should be sent by email to Dr Melanie Stefan:
[Email Address Removed]
Applicants must have:
- obtained, or expect to obtain, a first or 2.1 UK honours degree, or equivalent for degrees obtained outside the UK, in in neuroscience, computational neuroscience, biomedical sciences, computational biology, or a related subject
- good proficiency in at least one programming language
- working knowledge of neuroscience
- high proficiency in English (IELTS 6.5 with at least 6 in each component, or equivalent; see https://www.ed.ac.uk/studying/postgraduate/applying/your-application/entry-requirements/english-requirements)
An MSc in a relevant area, prior research experience in a related field and formal training in both biomedical sciences and computing or a quantitative subject are desirable.
To apply applicants should send a CV, the contact details of 2 references (including email address and phone number) and a covering letter, explaining why the applicant wishes to carry out this project, by email to Dr Melanie Stefan:
[Email Address Removed]
Please note, your application may be shared with the funders of this PhD Studentship, Medical Research Scotland and CERN openlab.
Interviews are expected to take place 3-4 weeks after the closing date for applications. In light of the current coronavirus situation, interviews may be conducted by video conference.
It is anticipated that the PhD Studentship will start in October 2020.
Centre for Discovery Brain Sciences at the University of Edinburgh: https://www.ed.ac.uk/discovery-brain-sciences
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