Subject: Post-doctoral research fellowship: modelling musical preference decisions From: Marcus Pearce <marcus.pearce@xxxxxxxx> Date: Sat, 11 Oct 2014 13:44:56 +0100 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>This is a multi-part message in MIME format. --------------020305010606070304030502 Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: quoted-printable Dear All (with apologies for cross-posting), We seek to appoint a Post-doctoral Research Fellow at Queen Mary,=20 University of London as part of an EPSRC-funded project=20 <http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=3DEP/M000702/1>on=20 predicting musical choices using computational models of cognitive and=20 neural processing. The goal of the project is to understand the=20 cognitive and neural processes involved in musical preference decisions=20 using computational modelling that incorporates the structure of the=20 music, the psychological state and traits of the listener and the=20 listening context. The successful candidate will be involved in the design and=20 implementation of the models, data collection from human listeners in=20 behavioural and EEG experiments, analysing the data to test the model=20 predictions, and writing up the results for publication in peer-reviewed=20 journals. Start date: 5 January 2015. Duration: 14 months (until March 5 2016).=20 Salary: =A334,283. For further information and to apply see:=20 http://music-cognition.eecs.qmul.ac.uk/postdoc.html Marcus --=20 Lecturer in Sound and Music Processing Queen Mary, University of London Mile End Road, London E1 4NS, UK Tel: +44 (0)20 7882 6207 Web: http://webprojects.eecs.qmul.ac.uk/marcusp Lab: http://music-cognition.eecs.qmul.ac.uk/ --------------020305010606070304030502 Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: 7bit <html> <head> <meta http-equiv="content-type" content="text/html; charset=ISO-8859-1"> </head> <body bgcolor="#FFFFFF" text="#000000"> Dear All (with apologies for cross-posting),<br> <br> <meta http-equiv="content-type" content="text/html; charset=ISO-8859-1"> We seek to appoint a Post-doctoral Research Fellow at Queen Mary, University of London as part of an <a href="http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/M000702/1" hrerf="http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/M000702/1">EPSRC-funded project</a><a hrerf="http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/M000702/1"> on predicting musical choices using computational models of cognitive and neural processing.</a> The goal of the project is to understand the cognitive and neural processes involved in musical preference decisions using computational modelling that incorporates the structure of the music, the psychological state and traits of the listener and the listening context. <br> <br> The successful candidate will be involved in the design and implementation of the models, data collection from human listeners in behavioural and EEG experiments, analysing the data to test the model predictions, and writing up the results for publication in peer-reviewed journals. <a hrerf="http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/M000702/1"><br> </a><br> <meta http-equiv="content-type" content="text/html; charset=ISO-8859-1"> Start date: 5 January 2015. Duration: 14 months (until March 5 2016). Salary: £34,283.<br> <br> For further information and to apply see: <a class="moz-txt-link-freetext" href="http://music-cognition.eecs.qmul.ac.uk/postdoc.html">http://music-cognition.eecs.qmul.ac.uk/postdoc.html</a><br> <br> Marcus<br> <pre class="moz-signature" cols="72">-- Lecturer in Sound and Music Processing Queen Mary, University of London Mile End Road, London E1 4NS, UK Tel: +44 (0)20 7882 6207 Web: <a class="moz-txt-link-freetext" href="http://webprojects.eecs.qmul.ac.uk/marcusp">http://webprojects.eecs.qmul.ac.uk/marcusp</a> Lab: <a class="moz-txt-link-freetext" href="http://music-cognition.eecs.qmul.ac.uk/">http://music-cognition.eecs.qmul.ac.uk/</a></pre> </body> </html> --------------020305010606070304030502--