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<div class="moz-text-html" lang="x-unicode"><b class="">Call
for postdoc applications in affective computing (Grenoble
Alps University)</b><br class="">
<br class="">
<b class="">Summary</b><br class="">
<br class="">
The Grenoble Alps University has an open position for a
highly motivated postdoc researcher. The
successful candidate will be working on the
multi-disciplinary research project THERADIA, which aims at
creating an adaptative virtual assistant that accompanies
patients suffering from cognitive disorders during the
completion of cognitive remediation exercises at home. The
person recruited will have the exciting opportunity to
develop new machine learning techniques for the robust
detection of affective behaviours from audiovisual data
collected in-the-wild. Models will be embodied in the
virtual agent to monitor and adapt the interaction with the
patient, and the whole system will be further tested in a
clinical trial to demonstrate the effectiveness of the agent
for accompanying patients suffering from
cognitive conditions during digital therapies.<br class="">
<br class="">
Duration: 2 years, salary: according to experience (up to
4142€ / month)
<div class=""><br class="">
<b class="">Scientific environment</b><br class="">
<br class="">
The person recruited will be hosted within the GETALP team
of the Laboratoire d’Informatique de Grenoble (LIG), which
offers a dynamic, international, and stimulating framework
for conducting high-level multi-disciplinary research. The
GETALP team is housed in a modern building (IMAG) located
on a 175-hectare landscaped campus that was ranked as the
eighth most beautiful campus in Europe by Times Higher
Education magazine in 2018.<br class="">
<br class="">
<b class="">Requirements</b><br class="">
<br class="">
The ideal candidate must have a PhD degree and a strong
background in machine learning, and affective computing or
cognitive science/neuroscience.<br class="">
<br class="">
The successful candidate should have:<br class="">
<br class="">
· Good knowledge of machine learning techniques<br
class="">
· Good knowledge of speech and image processing<br
class="">
· Good knowledge of experimental design and
statistics<br class="">
· Strong programming skills in Python<br class="">
· Excellent publication record<br class="">
· Willing to work in multi-disciplinary and
international teams<br class="">
· Good communication skills<br class="">
<br class="">
<b class="">Application</b><br class="">
<br class="">
Applications are expected to be received on an ongoing
basis and the position will be open until filled.
Applications should be sent to Fabien Ringeval (<a
href="mailto:fabien.ringeval@imag.fr" class=""
moz-do-not-send="true">fabien.ringeval@imag.fr</a>) and
François Portet (<a href="mailto:francois.portet@imag.fr"
class="" moz-do-not-send="true">francois.portet@imag.fr</a>).
The application file should contain:<br class="">
<br class="">
· Curriculum vitae<br class="">
· Recommendation letter<br class="">
· One-page summary of research background and
interests<br class="">
· At least three publications demonstrating expertise
in the aforementioned areas<br class="">
· Pre-defence reports and defence minutes; or summary
of the thesis with date of defence for those currently
in doctoral studies</div>
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