Subject: [AUDITORY] Funded PhD studentship in Neuro-Symbolic Models for Music Analysis (Durham University) From: Eamonn Bell <000001b18e8d47dc-dmarc-request@xxxxxxxx> Date: Tue, 7 Jun 2022 13:02:05 +0100--000000000000105b4c05e0da5c2b Content-Type: text/plain; charset="UTF-8" Dear list, We are advertising for a fully-funded PhD position, to develop novel algorithmic tools for music analysis using deep learning and structured/symbolic methods. It will combine approaches from computational musicology, image analysis, and natural language processing to advance the state of the art in the field. For more details, see: https://euraxess.ec.europa.eu/jobs/787162 Music analysis is a highly challenging task for which artificial intelligence (AI) and machine learning (ML) is lagging far behind the capabilities of human experts. Solving it requires a combination of two different model types: (1) neural networks and deep learning techniques to extract features from the input data and (2) structured graphical models and artificial grammars to represent the complex dependencies in a musical piece. The central goal of the project is to leverage the synergies from combining these techniques to build models that achieve human-expert level performance in analysing the structure of a musical piece. This studentship is fully funded under the EPSRC Doctoral Training Partnership scheme and is hosted at the Department of Computer Science at Durham University. There will be opportunities for collaboration with researchers in other departments, including the Department of Music. We require - enthusiasm for interdisciplinary research in artificial intelligence and music - an open mind-set and creative problem-solving skills - a solution-oriented can-do mentality - a desire to understand the structure of music and its inner workings - a good command of a modern programming language (preferably Python) and familiarity with a modern deep learning framework (e.g. PyTorch) - a strong master degree (or equivalent) with a significant mathematical or computational component Please send an email with your CV and a short informal motivation to Dr Robert Lieck robert.lieck@xxxxxxxx for initial discussions. We are looking to fill this position as soon as possible (the position is still open as long as it is advertised). The preferred start date is October 2022 (new academic year). Dr Robert Lieck Dr Eamonn Bell Department of Computer Science Durham University --000000000000105b4c05e0da5c2b Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr"><div dir=3D"ltr">Dear list,<br><br>We are advertising for = a fully-funded PhD position, to develop novel algorithmic tools for music a= nalysis using deep learning and structured/symbolic methods. It will combin= e approaches from computational musicology, image analysis, and natural lan= guage processing to advance the state of the art in the field.<div><br></di= v><div>For more details, see:=C2=A0<a href=3D"https://euraxess.ec.europa.eu= /jobs/787162">https://euraxess.ec.europa.eu/jobs/787162</a></div><div><br><= /div><div>Music analysis is a highly challenging task for which artificial = intelligence (AI) and machine learning (ML) is lagging far behind the capab= ilities of human experts. Solving it requires a combination of two differen= t model types: (1) neural networks and deep learning techniques to extract = features from the input data and (2) structured graphical models and artifi= cial grammars to represent the complex dependencies in a musical piece. <br= ><br>The central goal of the project is to leverage the synergies from comb= ining these techniques to build models that achieve human-expert level perf= ormance in analysing the structure of a musical piece. <br><br>This student= ship is fully funded under the EPSRC Doctoral Training Partnership scheme a= nd is hosted at the Department of Computer Science at Durham University. Th= ere will be opportunities for collaboration with researchers in other depar= tments, including the Department of Music.<br><br>We require<br><ul><li>ent= husiasm for interdisciplinary research in artificial intelligence and music= </li><li>an open mind-set and creative problem-solving skills</li><li>a sol= ution-oriented can-do mentality</li><li>a desire to understand the structur= e of music and its inner workings</li><li>a good command of a modern progra= mming language (preferably Python) and familiarity with a modern deep learn= ing framework (e.g. PyTorch)</li><li>a strong master degree (or equivalent)= with a significant mathematical or computational component</li></ul><br><b= r>Please send an email with your CV and a short informal motivation to Dr R= obert Lieck <a href=3D"mailto:robert.lieck@xxxxxxxx">robert.lieck@xxxxxxxx= m.ac.uk</a> for initial discussions. We are looking to fill this position a= s soon as possible (the position is still open as long as it is advertised)= . The preferred start date is October 2022 (new academic year).<br><br>Dr R= obert Lieck<br>Dr Eamonn Bell<br><br><br>Department of Computer Science<br>= Durham University</div></div></div> --000000000000105b4c05e0da5c2b--