[Eeglablist] Part-Time PhD Studentship/Part-Time EEG Technician: 6 year Job @ UEA

[Louis Renoult]

Hello,
Follow this link to see details of a Part-Time PhD Studentship/Part-Time
EEG Technician post at UEA (Application Deadline 23 September):
https://myview.uea.ac.uk/webrecruitment/pages/vacancy.jsf?vacancyRef=TC672
<https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fmyview.uea.ac.uk%2Fwebrecruitment%2Fpages%2Fvacancy.jsf%3FvacancyRef%3DTC672&data=02%7C01%7CL.Renoult%40uea.ac.uk%7Ce0e492a4ba1e4b7a51d408d736dc4145%7Cc65f8795ba3d43518a070865e5d8f090%7C0%7C0%7C637038191927847182&sdata=MAdUsj0l%2FJpWwxsIZCibM2UfAWhlNhlf89E%2Fkor54D8%3D&reserved=0>

For the PhD aspect potential projects include those described below.

Please contact Will Penny, Tom Sambrook or Malcolm Rae (copied in) for
further details.


*A Neuroeconomic Map of the Brain’s valuation centres.*
Supervisor – Dr Tom Sambrooke.

Decision-making in humans and other animals is heavily influenced by prior
experience with the decision problem at hand. Behavioural scientists have
traditionally
assumed that positive and negative outcomes previously arising from an
action are
combined into a single valuation indicating that action’s likely
profitability in the future
(cost-benefit analysis), thus providing a basis for rational choice between
actions.
Behavioural economics suggests no such integration occurs and our behaviour
is
determined by competition between cognitive controllers sensitive to reward
and
punishment. For your Ph.D. you will be a developing techniques to identify
these
controllers and profile them based on their neural activity in response to
reward (e.g.
money, tasty food, attractive images) and punishment (e.g. monetary loss,
electric
shock, bitter tastes).

Prerequisites: You should have a First Degree (minimum 2:1) in a relevant
subject
and have programming experience, ideally in MATLAB or R, and you must have a
master’s degree, with research methods training, ideally in Psychology or
relevant
discipline) in line with the academic requirements in the essential
criteria. You should
be willing to undergo psychology research training while doing your PhD.
Experience
with EEG acquisition and analysis would be beneficial but not essential



*Understanding Human Brain Dynamics: Statistical Machine Learning for
EEGanalysis.*
Supervisor – Professor William Penny.
Co-Supervisor: Louis Renoult

This project will leverage recent advances in statistical machine learning
to better
understand the neuronal processes that support perception, cognition and
action. The
study will be based on a specific machine learning architecture, called a
Variational
Auto-Encoder that is able to extract meaningful, low-dimensional
representations of
high-dimensional time-series data. The approach will be used to analyse
high-density
Electroencephalogram (EEG) data from cognitive neuroscience studies across a
range of paradigms (multi-sensory processing, autobiographical memory,
decision
making). This new framework will be validated in relation to current
standard
approaches based on Support Vector Machines and EEG source reconstruction.

Prerequisites: You should have a First degree (minimum 2:1) in Psychology,
Computer Science, Electronic Engineering or a related topic, along with
experience in
computer programming. You should also have a master’s degree with research
methods training with a dissertation mark of 65% or above.
Ideally, the candidate selecting this project will have an MSc in Cognitive
Neuroscience or related topic, and experience of EEG data acquisition,
experience
with Matlab, Machine learning, Statistical Parametric Mapping (SPM), and
knowledge
of EEGLab or Fieldtrip software. Co-authorship of previous academic papers
would
also be beneficial.


-- 
Louis Renoult, Ph.D.
Senior Lecturer
University of East Anglia,
School of Psychology
Lawrence Stenhouse Building (LSB)
Norwich Research Park,
Norwich
NR4 7TJ
United Kingdom