[AUDITORY] Deep learning postdoc positions at UCL (Nick Lesica )


Subject: [AUDITORY] Deep learning postdoc positions at UCL
From:    Nick Lesica  <lesica@xxxxxxxx>
Date:    Mon, 16 Oct 2023 09:37:08 +0100

--0000000000006a5c1f0607d1501b Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable We are seeking multiple postdoctoral researchers to join our work on the application of deep learning to the study of hearing and the design of assistive listening technologies. The work is supervised by Prof Nicholas Lesica at the UCL Ear Institute and will be carried out in partnership with Perceptual Technologies Ltd. and the UCLH Biomedical Research Centre. We are offering an opportunity to pursue a transformative solution to a major public health problem =E2=80=93= hearing loss =E2=80=93 that has the potential to benefit hundreds of millions of pe= ople, along with the potential to join a deep tech startup as part of the founding team upon project completion to commercialize the technology. *About the role* We have spent the past several years developing a unique capability for recording large-scale neural activity datasets with high spatiotemporal resolution (Armstrong et al., Nat Biomed Eng, 2022) and we recently demonstrated the power of applying deep learning to these datasets (Sabesan et al., eLife, 2023). We are now looking to realize the full potential of this combination of large-scale electrophysiology and deep learning for the development of transformative applications. Key duties and responsibilities will include: - Building data pipelines for processing large-scale neural activity recordings - Developing deep learning models to map sounds to neural activity and to transform sounds as required to create desired neural activity patterns - Analyzing neural recordings to assess the efficacy of new sound transformations in correcting neural distortions - Designing methods for the perceptual evaluation of new hearing technologies and working with our clinical partners to test patient benefit - Developing prototype hearing aid algorithms in preparation for commercialization The salary for this role is grade 7 (=C2=A340,524 =E2=80=93 =C2=A348,763 pe= r annum including London allowances) with salary on appointment dependent on experience. Funding is for up to two years in the first instance with potential for extension. This role meets the eligibility requirements for a skilled worker certificate of sponsorship or a global talent visa under UK Visas and Immigration legislation. Therefore, we welcome international applicants who require a visa. *About you* We are looking for deep learning experts who are interested in working with large-scale neural data to develop the next generation of hearing technologies, with significant autonomy in contributing to a radically new approach to sensory device design. The ideal candidates will have: - PhD in statistics, machine learning, computer science or related discipline - Experience working with high-dimensional datasets, and familiarity with modern deep learning workflows - Strong software engineering skills, experience working with the Python data science stack (numpy, scipy, sklearn, pytorch, tensorflow, etc.) - A knack for solving problems that are not amenable to off-the-shelf solutions - Experience modifying existing computational tools to solve new problems - Experience with audio processing in the context of hearing/audiology Please get in touch if you would like to discuss these opportunities ( lesica@xxxxxxxx). The application deadline is November 7, 2023. Interviews for shortlisted candidates will take place shortly thereafter. Start dates are flexible. Visit www.lesicalab.com/jobs for more information. 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 --0000000000006a5c1f0607d1501b Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">We are seeking multiple postdoctoral researchers to join o= ur work on the application of deep learning to the study of hearing and the= design of assistive listening technologies.<br><br>The work is supervised = by Prof Nicholas Lesica at the UCL Ear Institute and will be carried out in= partnership with Perceptual Technologies Ltd. and the UCLH Biomedical Rese= arch Centre. We are offering an opportunity to pursue a transformative solu= tion to a major public health problem =E2=80=93 hearing loss =E2=80=93 that= has the potential to benefit hundreds of millions of people, along with th= e potential to join a deep tech startup as part of the founding team upon p= roject completion to commercialize the technology.<br><br>*About the role*<= br><br>We have spent the past several years developing a unique capability = for recording large-scale neural activity datasets with high spatiotemporal= resolution (Armstrong et al., Nat Biomed Eng, 2022) and we recently demons= trated the power of applying deep learning to these datasets (Sabesan et al= ., eLife, 2023). We are now looking to realize the full potential of this c= ombination of large-scale electrophysiology and deep learning for the devel= opment of transformative applications.<br><br>Key duties and responsibiliti= es will include:<br><br>- Building data pipelines for processing large-scal= e neural activity recordings<br>- Developing deep learning models to map so= unds to neural activity and to transform sounds as required to create desir= ed neural activity patterns<br>- Analyzing neural recordings to assess the = efficacy of new sound transformations in correcting neural distortions<br>-= Designing methods for the perceptual evaluation of new hearing technologie= s and working with our clinical partners to test patient benefit<br>- Devel= oping prototype hearing aid algorithms in preparation for commercialization= <br><br><div>The salary for this role is grade 7 (=C2=A340,524 =E2=80=93 = =C2=A348,763 per annum including London allowances) with salary on appointm= ent dependent on experience. Funding is for up to two years in the first in= stance with potential for extension. This role meets the eligibility requir= ements for a skilled worker certificate of sponsorship or a global talent v= isa under UK Visas and Immigration legislation. Therefore, we welcome inter= national applicants who require a visa.<br><br>*About you*<br><br>We are lo= oking for deep learning experts who are interested in working with large-sc= ale neural data to develop the next generation of hearing technologies, wit= h significant autonomy in contributing to a radically new approach to senso= ry device design. The ideal candidates will have:<br><br>- PhD in statistic= s, machine learning, computer science or related discipline<br>- Experience= working with high-dimensional datasets, and familiarity with modern deep l= earning workflows<br>- Strong software engineering skills, experience worki= ng with the Python data science stack (numpy, scipy, sklearn, pytorch, tens= orflow, etc.)<br>- A knack for solving problems that are not amenable to of= f-the-shelf solutions<br>- Experience modifying existing computational tool= s to solve new problems<br>- Experience with audio processing in the contex= t of hearing/audiology</div><div><br>Please get in touch if you would like = to discuss these opportunities (<a href=3D"mailto:lesica@xxxxxxxx">lesica@xxxxxxxx= gmail.com</a>).<br><br>The application deadline is November 7, 2023. Interv= iews for shortlisted candidates will take place shortly thereafter. Start d= ates are flexible.<br><br>Visit <a href=3D"http://www.lesicalab.com/jobs">w= ww.lesicalab.com/jobs</a> for more information.</div><div><br clear=3D"all"= ><div><div dir=3D"ltr" class=3D"gmail_signature" data-smartmail=3D"gmail_si= gnature"><div dir=3D"ltr"><div><div dir=3D"ltr"><div><div dir=3D"ltr"><div>= <div dir=3D"ltr"><div><div dir=3D"ltr"><span><div><div dir=3D"ltr"><div>Bes= t wishes,<br></div><div><br>Nick<br><br>--<br><br>Nicholas A. Lesica, Ph.D.= </div><div>Professor of Neuroengineering</div><div><br></div><div>Ear Insti= tute<br>University College London<br>332 Gray&#39;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</a><br>Web: = =C2=A0=C2=A0=C2=A0 <a href=3D"http://www.lesicalab.com" target=3D"_blank">w= ww.lesicalab.com</a></div></div></div></span></div></div></div></div></div>= </div></div></div></div></div></div></div></div> --0000000000006a5c1f0607d1501b--


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