Research Assistant (PhD Student - Dr. -Ing.) or Postdoctoral Researcher ENT-Clinic (m/f/x)

Your tasks:

Develop three machine learning models (ML) for severity estimation of (1) disordered vocal fold dynamics based on clinical endoscopic high-speed imaging (4000 fps) and of (2) the acoustic voice quality based on the recorded acoustic signal and (3) of the overall phonation considering both imaging and acoustic data. Needed image processing and parameter computation methods have been developed in previous projects. Currently there are more than 100 parameters suggested for judgement, hence one important task is feature importance analysis to determine as few as possible and clinical interpretable parameters being used in the ML models. The goal is to develop models being robust and applicable for clinical use.

Supervision is enabled by the membership of Prof. Döllinger (supervisor) at the Technische Fakultät (Dep. Informatics and AIBE). Our team is highly interdisciplinary. Our division has several collaborations with technical and natural science chairs.

Essential experience/ qualifications:

• Graduation at a Master's level (or equivalent) in Computer Science, Mathematics, Artificial Intelligence, Life Science, Data Science or similar
• Machine learning, deep learning, … i.e. very good AI knowledge
• Good Programming skills (Python, C#/.NET)
• Structured and independent working practice, good communication and English skills