[AUDITORY] PhD position (Reminder / deadline extended): Speech Signal Processing for Clinical Voice Quality Characterisation @xxxxxxxx MUV, Vienna, Austria. (Philipp Aichinger )

Subject: [AUDITORY] PhD position (Reminder / deadline extended): Speech Signal Processing for Clinical Voice Quality Characterisation @xxxxxxxx MUV, Vienna, Austria.
From:    Philipp Aichinger  <philipp.aichinger@xxxxxxxx>
Date:    Mon, 10 Dec 2018 09:23:05 +0100
List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>

This is a multi-part message in MIME format.
--------------3A8B91DB4A37565CD65A7085
Content-Type: text/plain; charset=utf-8; format=flowed
Content-Transfer-Encoding: quoted-printable

Dear colleagues,

we are hiring a PhD candidate to work on clinical voice quality=20
characterisation at the Medical University of Vienna, Austria. This=20
project has a strong focus on auditory aspects of voice quality. We=20
would appreciate if you could forward the following announcement to=20
prospective applicants.

 >>>>>

    The Medical University of Vienna (MUV), Austria, seeks to fill a
    position of a PhD candidate within the project 'Objective
    differentiation of dysphonic voice quality types'. The candidate
    must hold a master=E2=80=99s degree, preferably in (one of) the field=
s of
    sound engineering, acoustical engineering, audio signal processing,
    or similar. The work will be conducted at the Division of
    Phoniatrics-Logopedics within the Department of Otorhinolaryngology
    of the MUV.

    The workgroup hosting the project is interested in the assessment of
    voice parameters relevant to the medical diagnosis and clinical care
    of voice disorders. A focus is given to functional assessment of
    voice, especially to the objective description of voice quality. The
    levels of description include kinematics of voice production, voice
    acoustics, and auditory perception of voice. Clinical studies are
    conducted with a laryngeal high-speed camera that records vocal fold
    vibration at 4000 frames per second. Microphone signals of the voice
    are recorded in parallel. Vibratory patterns of the vocal folds are
    analysed visually and computationally via modelling. Trajectories of
    vocal fold edges, spatial arrangements thereof, and glottal area
    waveforms are analysed. Regarding acoustics, analysis of audio
    recordings involves the implementation, testing, and training of
    specialized synthesizers for pathological voices. On the level of
    auditory perception, listening experiments are conducted, especially
    experiments involving discrimination tasks.

    Mandatory skills of the candidate are MATLAB programming, speech
    signal processing, psychoacoustics, good knowledge of English, good
    communication skills, and excellent analytical thinking. Optional
    skills of the candidate are knowledge of German, experience in a
    health care profession, image and video processing, Python,
    PureData, object-oriented programming, software engineering, version
    control (Subversion, Git, or similar), and SQL.

    The project duration is 4-5 years. The Austrian Science Fund (FWF)
    budgets for doctoral candidates a gross salary of 2.112,40 Euro per
    month. Application documents should be submitted to
    philipp.aichinger@xxxxxxxx

    Information regarding the living in Vienna, Austria, can be found at
    https://www.meduniwien.ac.at/web/en/international-affairs/living-in-v=
ienna/.

<<<<<

Kind regards,

--=20
MedUni Wien Signatur EN

*Univ.-Ass. DI Dr.techn. Philipp Aichinger*
Research Associate
PI Austrian Science Fund (FWF): KLI722-B30

*Medical University of Vienna*
Division of Phoniatrics-Logopedics
Department of Otorhinolaryngology

W=C3=A4hringer G=C3=BCrtel 18-20, 1090 Vienna, Austria
T: +43 (0)1 40400-11670
M: +43 (0)699 12 29 28 69
philipp.aichinger@xxxxxxxx=20
<mailto:philipp.aichinger@xxxxxxxx>
www.meduniwien.ac.at <http://www.meduniwien.ac.at>

MedUni_Wien_Hauptlogo_EN

--------------3A8B91DB4A37565CD65A7085
Content-Type: multipart/related;
 boundary="------------9252DD662752D7F2C82C1F1F"


--------------9252DD662752D7F2C82C1F1F
Content-Type: text/html; charset=utf-8
Content-Transfer-Encoding: quoted-printable

<html>
  <head>

    <meta http-equiv=3D"content-type" content=3D"text/html; charset=3DUTF=
-8">
  </head>
  <body text=3D"#000000" bgcolor=3D"#FFFFFF">
    <p>Dear colleagues,</p>
    <p>we are hiring a PhD candidate to work on clinical voice quality
      characterisation at the Medical University of Vienna, Austria.
      This project has a strong focus on auditory aspects of voice
      quality. We would appreciate if you could forward the following
      announcement to prospective applicants.</p>
    <p>&gt;&gt;&gt;&gt;&gt;<br>
    </p>
    <blockquote>
      <p>The Medical University of Vienna (MUV), Austria, seeks to fill
        a position of a PhD candidate within the project 'Objective
        differentiation of dysphonic voice quality types'. The candidate
        must hold a master=E2=80=99s degree, preferably in (one of) the f=
ields
        of sound engineering, acoustical engineering, audio signal
        processing, or similar. The work will be conducted at the
        Division of Phoniatrics-Logopedics within the Department of
        Otorhinolaryngology of the MUV.</p>
      <p>The workgroup hosting the project is interested in the
        assessment of voice parameters relevant to the medical diagnosis
        and clinical care of voice disorders. A focus is given to
        functional assessment of voice, especially to the objective
        description of voice quality. The levels of description include
        kinematics of voice production, voice acoustics, and auditory
        perception of voice. Clinical studies are conducted with a
        laryngeal high-speed camera that records vocal fold vibration at
        4000 frames per second. Microphone signals of the voice are
        recorded in parallel. Vibratory patterns of the vocal folds are
        analysed visually and computationally via modelling.
        Trajectories of vocal fold edges, spatial arrangements thereof,
        and glottal area waveforms are analysed. Regarding acoustics,
        analysis of audio recordings involves the implementation,
        testing, and training of specialized synthesizers for
        pathological voices. On the level of auditory perception,
        listening experiments are conducted, especially experiments
        involving discrimination tasks.</p>
      <p>Mandatory skills of the candidate are MATLAB programming,
        speech signal processing, psychoacoustics, good knowledge of
        English, good communication skills, and excellent analytical
        thinking. Optional skills of the candidate are knowledge of
        German, experience in a health care profession, image and video
        processing, Python, PureData, object-oriented programming,
        software engineering, version control (Subversion, Git, or
        similar), and SQL.</p>
      <p>The project duration is 4-5 years. The Austrian Science Fund
        (FWF) budgets for doctoral candidates a gross salary of 2.112,40
        Euro per month. Application documents should be submitted to <a>p=
hilipp.aichinger@xxxxxxxx</a></p>
      <p>Information regarding the living in Vienna, Austria, can be
        found at <a
href=3D"https://www.meduniwien.ac.at/web/en/international-affairs/living-=
in-vienna/">https://www.meduniwien.ac.at/web/en/international-affairs/liv=
ing-in-vienna/</a>.</p>
    </blockquote>
    <p> &lt;&lt;&lt;&lt;&lt;</p>
    <p>Kind regards,<br>
    </p>
    <div class=3D"moz-signature">-- <br>
      <title>MedUni Wien Signatur EN</title>
      <span style=3D"font-family:'Lucida Sans';font-size:10;color:#111d4e=
">
        <p> <b>Univ.-Ass. DI Dr.techn. Philipp Aichinger</b> <br>
          Research Associate <br>
          PI Austrian Science Fund (FWF): KLI722-B30 </p>
        <p> <b>Medical University of Vienna</b> <br>
          Division of Phoniatrics-Logopedics <br>
          Department of Otorhinolaryngology </p>
        <p> W=C3=A4hringer G=C3=BCrtel 18-20, 1090 Vienna, Austria <br>
          T: +43 (0)1 40400-11670 <br>
          M: +43 (0)699 12 29 28 69 <br>
          <a href=3D"mailto:philipp.aichinger@xxxxxxxx">philipp.a=
ichinger@xxxxxxxx</a>
          <br>
          <a href=3D"http://www.meduniwien.ac.at">www.meduniwien.ac.at</a=
>
        </p>
        <img src=3D"cid:part5.E676403E.DA38C2EB@xxxxxxxx"
          alt=3D"MedUni_Wien_Hauptlogo_EN"> </span>
    </div>
  </body>
</html>

--------------9252DD662752D7F2C82C1F1F
Content-Type: image/png;
 name="oiidnllgdcomfdpa.png"
Content-Transfer-Encoding: base64
Content-ID: <part5.E676403E.DA38C2EB@xxxxxxxx>
Content-Disposition: inline;
 filename="oiidnllgdcomfdpa.png"
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--------------9252DD662752D7F2C82C1F1F--

--------------3A8B91DB4A37565CD65A7085--