Subject: [AUDITORY] Postdoc position at the UCL Ear Institute From: Nick Lesica <lesica@xxxxxxxx> Date: Mon, 21 Nov 2022 17:19:55 +0000--00000000000058f33705edfe4462 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable We are currently recruiting a postdoctoral research associate to work on a project entitled =E2=80=9CCharacterizing the effects of hearing loss and he= aring aids on the neural code for music=E2=80=9D. The project is jointly supervised by Prof Nicholas Lesica at the UCL Ear Institute (lesicalab.com) and Dr. Alinka Greasley at the University of Leeds who leads the Hearing Aids for Music Project (musicandhearingaids.org ). What=E2=80=99s the problem? Distorted music perception is a major problem for the hard of hearing and current hearing aids often fail to help. But without a detailed understanding of the auditory processing of music and how it is disrupted by hearing loss, it remains unclear how the benefits of hearing aids for music can be improved. We aim to characterize the neural code that forms the brain=E2=80=99s internal representation of music to identify the featur= es that underlie normal and impaired perception and to develop specific design targets for new hearing aids. What=E2=80=99s the opportunity? The project will make use of novel methods for large-scale electrophysiology in animal models of human hearing that we have recently developed (see Armstrong et al., Nat Biomed Eng, 2022). These methods allow us to collect unique datasets containing the activity of hundreds of auditory neurons over many hours. The postholder=E2=80=99s primary duty wil= l be to analyze these datasets to characterize the neural code at both the single neuron and network level and to link the results to the real-world experiences of human listeners based on a large-scale psychoacoustics dataset. Who are we looking for? The ideal candidate will have expertise in statistical and machine learning methods for large-scale data analysis and experience applying these methods in the context of music, audio, hearing, and/or neuroscience. What will you do? - Build data pipelines for processing large-scale neural activity recording= s - Develop models to analyze the mapping from sounds to neural activity - Identify the distortions in the neural code that underlie impaired perception - Design new sound transformations for correcting distortions in the neural code What are we offering? - An opportunity to help develop transformative solutions to a major public health problem that has the potential to benefit hundreds of millions of people - A chance to join a dynamic entrepreneurial team at one of the world=E2=80= =99s largest hearing research centers - Salary at UCL Grade 7, which ranges from =C2=A338,308- =C2=A346,155 per a= nnum - UCL staff benefits (click here for more info) Please get in touch if you would like to discuss these opportunities ( lesica@xxxxxxxx). Official application portal: https://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?jobId=3D1349 Application deadline: 4 December, 2022 Best wishes, Nick -- Nicholas A. Lesica, Ph.D. Professor of Neuroengineering Ear Institute University College London 332 Gray's Inn Rd. London, WC1X 8EE, UK Phone: +44 (0)20 7679 8979 Email: lesica@xxxxxxxx Web: www.lesicalab.com --00000000000058f33705edfe4462 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr"><div>We are currently recruiting a postdoctoral research a= ssociate to work on a project entitled =E2=80=9CCharacterizing the effects = of hearing loss and hearing aids on the neural code for music=E2=80=9D.<br>= <br>The project is jointly supervised by Prof Nicholas Lesica at the UCL Ea= r Institute (<a href=3D"http://lesicalab.com">lesicalab.com</a>) and Dr. Al= inka Greasley at the University of Leeds who leads the Hearing Aids for Mus= ic Project (<a href=3D"http://musicandhearingaids.org">musicandhearingaids.= org</a>).<br><br>What=E2=80=99s the problem?<br><br>Distorted music percept= ion is a major problem for the hard of hearing and current hearing aids oft= en fail to help. But without a detailed understanding of the auditory proce= ssing of music and how it is disrupted by hearing loss, it remains unclear = how the benefits of hearing aids for music can be improved. We aim to chara= cterize the neural code that forms the brain=E2=80=99s internal representat= ion of music to identify the features that underlie normal and impaired per= ception and to develop specific design targets for new hearing aids.<br><br= >What=E2=80=99s the opportunity?<br><br>The project will make use of novel = methods for large-scale electrophysiology in animal models of human hearing= that we have recently developed (see Armstrong et al., Nat Biomed Eng, 202= 2). These methods allow us to collect unique datasets containing the activi= ty of hundreds of auditory neurons over many hours. The postholder=E2=80=99= s primary duty will be to analyze these datasets to characterize the neural= code at both the single neuron and network level and to link the results t= o the real-world experiences of human listeners based on a large-scale psyc= hoacoustics dataset.<br><br>Who are we looking for?<br><br>The ideal candid= ate will have expertise in statistical and machine learning methods for lar= ge-scale data analysis and experience applying these methods in the context= of music, audio, hearing, and/or neuroscience.<br><br>What will you do?<br= ><br>- Build data pipelines for processing large-scale neural activity reco= rdings<br>- Develop models to analyze the mapping from sounds to neural act= ivity<br>- Identify the distortions in the neural code that underlie impair= ed perception<br>- Design new sound transformations for correcting distorti= ons in the neural code<br><br></div><div>What are we offering?<br><br>- An = opportunity to help develop transformative solutions to a major public heal= th problem that has the potential to benefit hundreds of millions of people= <br>- A chance to join a dynamic entrepreneurial team at one of the world= =E2=80=99s largest hearing research centers<br>- Salary at UCL Grade 7, whi= ch ranges from =C2=A338,308- =C2=A346,155 per annum<br>- UCL staff benefits= (click here for more info)</div><div><br>Please get in touch if you would = like to discuss these opportunities (<a href=3D"mailto:lesica@xxxxxxxx">le= sica@xxxxxxxx</a>).<br><br>Official application portal:=C2=A0<a href=3D"ht= tps://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?jobId=3D1349">https= ://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?jobId=3D1349</a><br></= div><div><br></div><div>Application deadline: 4 December, 2022=C2=A0</div><= br clear=3D"all"><div><div dir=3D"ltr" class=3D"gmail_signature" data-smart= mail=3D"gmail_signature"><div dir=3D"ltr"><div><div dir=3D"ltr"><div><div d= ir=3D"ltr"><div><div dir=3D"ltr"><div><div dir=3D"ltr"><span><div><div dir= =3D"ltr"><div>Best wishes,<br></div><div><br>Nick<br><br>--<br><br>Nicholas= A. Lesica, Ph.D.</div><div>Professor of Neuroengineering</div><div><br></d= iv><div>Ear Institute<br>University College London<br>332 Gray's Inn Rd= .<br>London, WC1X 8EE, UK<br><br>Phone: +44 (0)20 7679 8979<br>Email:=C2=A0= =C2=A0 <a href=3D"mailto:lesica@xxxxxxxx" target=3D"_blank">lesica@xxxxxxxx= om</a><br>Web: =C2=A0=C2=A0=C2=A0 <a href=3D"http://www.lesicalab.com" targ= et=3D"_blank">www.lesicalab.com</a></div></div></div></span></div></div></d= iv></div></div></div></div></div></div></div></div></div> --00000000000058f33705edfe4462--