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

Louis Renoult renoult.louis at gmail.com
Wed Sep 11 12:48:01 PDT 2019

Follow this link to see details of a Part-Time PhD Studentship/Part-Time
EEG Technician post at UEA (Application Deadline 23 September):

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
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
Behavioural economics suggests no such integration occurs and our behaviour
determined by competition between cognitive controllers sensitive to reward
punishment. For your Ph.D. you will be a developing techniques to identify
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,
shock, bitter tastes).

Prerequisites: You should have a First Degree (minimum 2:1) in a relevant
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
discipline) in line with the academic requirements in the essential
criteria. You should
be willing to undergo psychology research training while doing your PhD.
with EEG acquisition and analysis would be beneficial but not essential

*Understanding Human Brain Dynamics: Statistical Machine Learning for
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
Auto-Encoder that is able to extract meaningful, low-dimensional
representations of
high-dimensional time-series data. The approach will be used to analyse
Electroencephalogram (EEG) data from cognitive neuroscience studies across a
range of paradigms (multi-sensory processing, autobiographical memory,
making). This new framework will be validated in relation to current
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,
with Matlab, Machine learning, Statistical Parametric Mapping (SPM), and
of EEGLab or Fieldtrip software. Co-authorship of previous academic papers
also be beneficial.

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

More information about the eeglablist mailing list