Subject: [AUDITORY] Post-doc position available: computational audiology From: Anna Warzybok-Oetjen <anna.warzybok-oetjen@xxxxxxxx> Date: Mon, 18 Jul 2022 06:49:42 +0000--_000_98de285fcdf84be5a149570340741e21unioldenburgde_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Dear colleagues, we have a post-doc position available for three years in the group of medic= al physics (B. Kollmeier) at the CvO Universit=E4t Oldenburg, Germany (htt= ps://uol.de/stellen?stelle=3D68955) - see details below . Please share with= everyone who might be interested! Many thanks, Anna Warzybok ------------------------------ In the Cluster of Excellence Hearing4All at the Carl von Ossietzky Universi= ty of Oldenburg, Faculty VI, Department of Medical Physics and Acoustics (D= MPA), Department of Medical Physics (Prof. Kollmeier), we seek for a Postdoctoral researcher in computational audiology (m/f/d, salary according to E13 TV-L,100%) The position is suitable for part-time work and should be filled as soon as= possible for a period of three years. It is aimed at applicants who have e= xtensive knowledge in the fields of statistical audiology, auditory modelli= ng, audiological diagnostics, and hearing aid parameter setting and are wil= ling to participate in the teaching tasks of the DMPA. As part of a DFG-funded project related to statistical and precision audiol= ogy the position will focus on data conditioning and audiological profile a= nalysis for the diagnosis and compensation of hearing impairment. The succe= ssful candidate should contribute to strengthening the link between audiolo= gical measures and parameter setting of hearing aids. Furthermore, this sho= uld ideally include statistical and/or auditory modelling as objective meas= ures supporting the efficiency of hearing diagnostics and optimizing the pr= escription and fitting of modern hearing devices (see below for a descripti= on of the project). Candidates are expected to have an academic university degree (PhD degree a= nd Master or Diploma degree) in Hearing Technology & Audiology, Biomedical = Physics, Engineering Physics, Data Science or a related discipline and have= shown their ability to perform excellent scientific work, usually demonstr= ated by the outstanding quality of their Doctorate/PhD research and a good = publication record. The successful candidate will have extensive knowledge in at least two of t= he following research fields: statistical modelling, auditory modelling, au= diological diagnostics, hearing device parameter selection. A strong intere= st in interdisciplinary and application-oriented work, familiarity with sci= entific tools and programming languages, as well as good spoken and written= English language skills are required. German language skills are desirable= but not obligatory. The University of Oldenburg is dedicated to increasing the percentage of wo= men in science. Therefore, female candidates are particularly encouraged to= apply. In accordance with Lower Saxony regulations (=A7 21 Section 3 NHG) = female candidates with equal qualifications will be preferentially consider= ed. Applicants with disabilities will be given preference in case of equal = qualification. Applications with cover letter, CV in tabular form, publication list, and c= opies of certificates for academic grades are requested by 22.08.2022 (pref= erably by E-Mail as one PDF-file) to: Prof. Dr.rer.nat. Dr.med. Birger Kollmeier, E-mail: birger.kollmeier@xxxxxxxx= <mailto:birger.kollmeier@xxxxxxxx> Medizinische Physik und Exzellenzcluster Hearing4all Universit=E4t Oldenburg D - 26111 Oldenburg Prof. Kollmeier (birger.kollmeier@xxxxxxxx) can be contacted for further ques= tions regarding the position. Project Summary Even though hearing impairment is the most common sensory disease with a ma= ssive negative impact on approximately 18% of our population, the diagnosti= cs and rehabilitation approaches with hearing devices are still limited, e.= g., the restoration of normal speech perception in everyday noisy conditio= ns is still incomplete - primarily because of the scattered empirical knowl= edge about the reduced speech perception and the limited individual benefit= from a hearing device without a systematic data analysis approach. The cur= rent project addresses this problem in a statistical, machine-learning-guid= ed way that combines basic science, statistical analysis, and clinical audi= ology independent from the test language employed: By building up an exchan= geable, easily accessible, and expandable database of audiological diagnost= ic measures and specialized, language-independent tests applied to a clinic= al population, we will analyze the causes and consequences of hearing impai= rment in a precise and individualized manner. Statistical and machine-learn= ing methods will be used to identify a minimum set of measures needed for t= he diagnosis of a given hearing disorder with high certainty. This should l= ead to statistically motivated auditory profiles which will be linked to in= dividualized treatment recommendations and fitting of hearing devices that = are verified using an idealized, laboratory-based "open master hearing aid"= (Grimm et al., 2006) in comparison to the benefit provided by the patient= =B4s own device. Hence, using only a few specific audiological tests in par= ameter selection and assessing the benefit from hearing devices, a more com= prehensive and theory-grounded way of hearing rehabilitation will be reache= d, thus increasing the efficiency and acceptance of hearing devices. Genera= lly, this statistical audiology approach will lead to a precise and efficie= nt diagnostics and an optimized prescription and fitting of modern hearing = devices. --_000_98de285fcdf84be5a149570340741e21unioldenburgde_ Content-Type: text/html; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable <html> <head> <meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Diso-8859-= 1"> <style type=3D"text/css" style=3D"display:none;"><!-- P {margin-top:0;margi= n-bottom:0;} --></style> </head> <body dir=3D"ltr"> <div id=3D"divtagdefaultwrapper" style=3D"font-size:12pt;color:#000000;font= -family:Calibri,Helvetica,sans-serif;" dir=3D"ltr"> <div style=3D"color: rgb(0, 0, 0);"> <div id=3D"divRplyFwdMsg" dir=3D"ltr"> <div> </div> </div> <div> <div id=3D"divtagdefaultwrapper" dir=3D"ltr" style=3D"font-size:12pt; color= :#000000; font-family:Calibri,Helvetica,sans-serif"> <p></p> <p>Dear colleagues,</p> <p>we have a post-doc position available for three years in the group of me= dical physics (B. Kollmeier) at the CvO Universit=E4t Oldenburg, Germany&nb= sp; (<a href=3D"https://uol.de/stellen?stelle=3D68955" class=3D"OWAAutoLink= " id=3D"LPlnk576470" previewremoved=3D"true">https://uol.de/stellen?stelle= =3D68955</a>) - see details below . Please share with everyone who might be interested!<= /p> <p><br> </p> <p>Many thanks,</p> Anna Warzybok <p></p> <p>------------------------------<br> </p> <p><br> </p> <p></p> <div class=3D"stellentext"> <p>In the Cluster of Excellence Hearing4All at the Carl von Ossietzky Unive= rsity of Oldenburg, Faculty VI, Department of Medical Physics and Acoustics= (DMPA), Department of Medical Physics (Prof. Kollmeier), we seek for a</p> <p><strong>Postdoctoral researcher in computational audiology </strong></p> <p>(m/f/d, salary according to E13 TV-L,100%) </p> <p><strong></strong></p> <p>The position is suitable for part-time work and should be filled as soon= as possible for a period of three years. It is aimed at applicants who hav= e extensive knowledge in the fields of <strong>statistical audiology, auditory modelling, audiological diagnostics= , and hearing aid parameter setting</strong> and are willing to participate= in the teaching tasks of the DMPA. </p> <p>As part of a DFG-funded project related to statistical and precision aud= iology the position will focus on data conditioning and audiological profil= e analysis for the diagnosis and compensation of hearing impairment. The su= ccessful candidate should contribute to strengthening the link between audiological measures and parameter sett= ing of hearing aids. Furthermore, this should ideally include statistical a= nd/or auditory modelling as objective measures supporting the efficiency of= hearing diagnostics and optimizing the prescription and fitting of modern hearing devices (see below for a de= scription of the project). </p> <p>Candidates are expected to have an academic university degree (PhD degre= e and Master or Diploma degree) in Hearing Technology & Audiology, Biom= edical Physics, Engineering Physics, Data Science or a related discipline a= nd have shown their ability to perform excellent scientific work, usually demonstrated by the outstanding quality= of their Doctorate/PhD research and a good publication record. </p> <p>The successful candidate will have extensive knowledge <u>in at least tw= o</u> of the following research fields: statistical modelling, auditory mod= elling, audiological diagnostics, hearing device parameter selection. A str= ong interest in interdisciplinary and application-oriented work, familiarity with scientific tools and progr= amming languages, as well as good spoken and written English language skill= s are required.<a name=3D"_Hlk95747991"> German language skills are desirab= le but not obligatory.</a></p> <p>The University of Oldenburg is dedicated to increasing the percentage of= women in science. Therefore, female candidates are particularly encouraged= to apply. In accordance with Lower Saxony regulations (=A7 21 Section 3 NH= G) female candidates with equal qualifications will be preferentially considered. Applicants with disabilities will be gi= ven preference in case of equal qualification.</p> <p>Applications with cover letter, CV in tabular form, publication list, an= d copies of certificates for academic grades are requested by <strong>22.08.2022</strong> (preferably by E-Mail as <strong>one PDF-file</= strong>) to: </p> <p>Prof. Dr.rer.nat. Dr.med. Birger Kollmeier, E-mail: <a href=3D"mailto:bi= rger.kollmeier@xxxxxxxx"> birger.kollmeier@xxxxxxxx</a></p> <p>Medizinische Physik und Exzellenzcluster Hearing4all</p> <p>Universit=E4t Oldenburg</p> <p>D - 26111 Oldenburg</p> <p>Prof. Kollmeier (birger.kollmeier@xxxxxxxx) can be contacted for further q= uestions regarding the position.</p> <p class=3D"Default"><strong>Project Summary<br> </strong>Even though hearing impairment is the most common sensory disease = with a massive negative impact on approximately 18% of our population, the = diagnostics and rehabilitation approaches with hearing devices are still li= mited, e. g., the restoration of normal speech perception in everyday noisy conditions is still incomplete = - primarily because of the scattered empirical knowledge about the reduced = speech perception and the limited individual benefit from a hearing device = without a systematic data analysis approach. The current project addresses this problem in a statistical, mac= hine-learning-guided way that combines basic science, statistical analysis,= and clinical audiology independent from the test language employed: By bui= lding up an exchangeable, easily accessible, and expandable database of audiological diagnostic measures an= d specialized, language-independent tests applied to a clinical population,= we will analyze the causes and consequences of hearing impairment in a pre= cise and individualized manner. Statistical and machine-learning methods will be used to identify a minimu= m set of measures needed for the diagnosis of a given hearing disorder with= high certainty. This should lead to statistically motivated auditory profi= les which will be linked to individualized treatment recommendations and fitting of hearing devices that are verified= using an idealized, laboratory-based "open master hearing aid" (= Grimm et al., 2006) in comparison to the benefit provided by the patient=B4= s own device. Hence, using only a few specific audiological tests in parameter selection and assessing the benefit from h= earing devices, a more comprehensive and theory-grounded way of hearing reh= abilitation will be reached, thus increasing the efficiency and acceptance = of hearing devices. Generally, this statistical audiology approach will lead to a precise and efficient diagno= stics and an optimized prescription and fitting of modern hearing devices.<= /p> </div> <br> <p></p> </div> </div> </div> </div> </body> </html> --_000_98de285fcdf84be5a149570340741e21unioldenburgde_--