Postdoc: Multimodal Language & Brain Dynamics (RIFT-EEG)

Radboud University Nijmegen via AcademicTransfer

Netherlands

Vor Ort

EUR 42.000 - 60.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Benefits dieser Stelle

8% holiday allowance
8.3% end-of-year bonus
Extra days off (30 or 41 days)

Zusammenfassung

Radboud University Nijmegen invites applications for a postdoctoral researcher at the intersection of language, communication and cognitive neuroscience. You will investigate how the human brain integrates speech with gestures and lip movements using EEG and MEG, rapid invisible frequency tagging, MVPA and mTRFs to reveal neural dynamics of multimodal processing.

The ideal candidate holds a PhD in neurolinguistics and has strong programming skills in Python/MATLAB/R, plus experience with

Qualifikationen

  • Completed a PhD in neurolinguistics.
  • Strong programming skills in Python and/or MATLAB and/or R.
  • Experience with multimodal communication and language processing.
  • Familiarity with statistical modelling (e.g. MVPA, regression).
  • Interest in neural oscillations and neural dynamics during language processing.

Aufgaben

  • Investigate how the brain integrates speech with visual signals during communication.
  • Conduct RIFT-EEG experiments on multimodal communication.
  • Analyze EEG/MEG data with MVPA, mTRFs and other modern methods.
  • Develop methods to provide causal evidence for neural oscillations in multimodal processing.

Kenntnisse

Python
MATLAB
R
Multimodal processing
Statistical modelling
OpenPose
OpenFace

Ausbildung

PhD in neurolinguistics

Tools

MVPA
mTRFs
EEG/MEG data analysis
RIFT-EEG
OpenPose
OpenFace

Jobbeschreibung

Radboud University Nijmegen invites applications for a postdoctoral researcher at the intersection of language, communication and cognitive neuroscience. You will investigate how the human brain integrates speech with gestures and lip movements using EEG and MEG, rapid invisible frequency tagging, MVPA and mTRFs to reveal neural dynamics of multimodal processing.

The ideal candidate holds a PhD in neurolinguistics and has strong programming skills in Python/MATLAB/R, plus experience with

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