PhD Developing novel methods for analysing multi-modal and multi-scale neural recordings

Closing Date

30 Nov 2018

Address

School of Informatics, University of Edinburgh

Project Description

About the studentship 

Advances in data acquisition technologies lead to the availability of ever more complex datasets. Often, the gathered variables have fundamentally different statistics. In many domains, the relationships between the recorded variables are of particular importance and also changing in time. One such domain is computational neuroscience where it was recently shown that even in early sensory brain areas, neural responses to stimuli are modulated by behavioural context. The precise functional interactions underlying this modulation are currently unknown but nonetheless important for understanding how the amazing versatility of sensory processing comes about. From an analytical point of view, understanding the complex interactions between neural activity, behaviour and task variables, all being subject to different statistics and timescales, is a major challenge. 

In this project, the successful applicant will develop and apply novel methods for analysing multi-modal and multi-scale neural recordings as motivated by the context-dependent sensory processing problem encountered in neuroscience. In particular, the successful candidate will devise new probabilistic models and Bayesian inference schemes with an emphasis on applicability to big heterogeneous datasets. Specific datasets consist of calcium-imaging or multi-electrode recordings of large populations of neurons as well as concurrently recorded behavioural data collected from rodents. The project is highly interdisciplinary, bridging computational neuroscience, statistical modelling and machine learning. Our group collaborates closely with the experimental groups of Nathalie Rochefort (University of Edinburgh, joint EPSRC-funded project to start in March) and Shuzo Sakata (University of Strathclyde). The successful applicant will join the Institute for Adaptive and Neural Computation which hosts strong research groups in the relevant fields. 

http://www.anc.ed.ac.uk/ 

Background / skills required 
Applicants should have a strong quantitative background (e.g. math, statistics, computer science, physics, computational neuroscience), good programming skills and a keen interest in interdisciplinary research. A background in neuroscience is desirable, but not essential. 

How to apply 
Interested applicants should submit their application to the Institute for Adaptive and Neural Computation. https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&edition=2018&id=489 
For further information, please contact Arno Onken (aonken@inf.ed.ac.uk). 
 

Funding Notes

Eligibility 
The position is available to UK/EU applicants. Other excellent applicants may be eligible for international postgraduate scholarships - please get in touch. The start date is flexible. 

Contact Details

Arno Onken: aonken@inf.ed.ac.uk