Research associate (PhD Candidate)
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Info und Anleitung Info and instruction
The University of Oldenburg is seeking to fill the following position:
Paygrade
E13
Working Hours
75%
Institution
School VI of Medicine and Health Sciences, Department of Medical Physics and Acoustics, Computational Audition Group
Location
Oldenburg (Old)
Application Deadline- 12.2024
First day of work
as soon as possible
Limited
for 3 years
About us
The position is part of the DFG-funded Collaborative Research Centre SFB 1330 "Hearing Acoustics" ( https://uol.de/sfb1330/bereich-b-algorithmen ) at the Department of Medical Physics and Acoustics, Faculty VI. Within project B3 of the research centre, the Computational Audition Group develops machine learning algorithms for signal processing of speech and audio data.
Your tasks
The position aims at conducting research into deep learning-based signal processing algorithms for speech enhancement and computational auditory scene analysis. Deep networks such as U-nets and transformers are used to extract information about an acoustic scene, including enhancement of speech from noise, classification of speech and noise sources, and source localization.
You will devise, implement and train deep network models and use them on large-scale real-environment audio data.
Quantitative methods for post-hoc analysis of network models after training will be developed to interpret the signal processing steps that the network has learned, e.g., to extract a speech signal from an acoustic scene.
Reduced models suitable for real-time applications such as hearing aids and headsets will be derived from developed algorithms.
You will publish your findings in scientific papers for international conferences and journals.
Participation in research meetings of the Collaborative Research Centre Hearing Acoustics and the Department of Medical Physics and Acoustics are expected.
The position is expected to lead to a Ph.D. degree.
Your profile
University degree (Diploma (Univ.)/ Master) in Engineering, Computer Science, Physics, Mathematics, or related fields.
Excellent command of written and spoken English.
Theoretical and practical knowledge in the fields of signal processing, machine learning, statistics, especially in the area of deep neural networks.
Very good programming skills in Python and in the PyTorch machine learning framework.
High degree of independence, flexibility, and teamwork skills, as well as willingness to work in an interdisciplinary manner.
Experience with scientific presentations and publications is desirable.
We Offer
Work in a state-of-the-art and challenging research field.
A dynamic research environment in the Collaborative Research Centre Hearing Acoustics and the Department of Medical Physics and Acoustics.
State-of-the-art research facilities.
GPU computing facilities with dedicated A100s and shared HPC-cluster with H100s.
Salary according to TVL-E13 (75%), i.e., minimum 3472 Euros per month plus benefits before tax (exact amount depending on experience and qualifications).
Our standards
The University of Oldenburg is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. In accordance to § 21 Section 3 NHG, female candidates with equal qualifications will be preferentially considered.Applicants with disabilities will be given preference in case of equal qualification.
Further information
The position is part of the Collaborative Research Centre Hearing Acoustics ("Sonderforschungsbereich Hörakustik, SFB 1330"), funded by the German federal research agency (DFG). Within the centre, it conducts research in project "B3 - Hierarchical models of acoustic information processing and their application for source detection and enhancement", headed by Dr.Jörn Anemüller.
Contact:
For further information or questions, please contact Priv.-Doz. Dr. Jörn Anemüller, joern.anemueller [at] uni-oldenburg.de .
Please send your application via e-mail by 06.12.2024 to
joern.anemueller [at] uni-oldenburg.de
Please send your application (ref. SFB-B3-1280) including a letter of motivation, curriculum vitae, list of publications, and a copy of the university diplomas and grades - preferably by email (max. 2 pdf files up to 10 MB) - to Dr. Jörn Anemüller, joern.anemueller [at] uni-oldenburg.de , with copy to sfb1330-admin [at] uni-oldenburg.de , Dept. Medical Physics and Acoustics, Carl-von-Ossietzky-Str.9-11, 26111 Oldenburg.
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- Reference: jobs.myscience.de/id201854