Research assistant

In a project funded by the German Research Foundation, you will work together with the project
partner Fraunhofer IWS and various industry partners on an acoustic monitoring and control
system for industrial laser processes. Distributed microphone arrays will be used to capture and
characterize acoustic emissions from the machining process with high spatial resolution under
real production conditions in real time. Fast data-driven algorithms using transformer
architectures will be applied for signal processing.

• Contributing to the design and implementation of the required microphone arrays
• Creating synthetic datasets for training with Acoupipe
• Planning and conducting measurement campaigns to create training datasets in the laboratory and in industrial environments
• Training machine learning models and adapting pretrained models for improved generalization using DIL and TTA
• Contributing to system integration and validation

• Successfully completed academic university degree (Master, Diplom, or equivalent) in an
  engineering or mathematical discipline
• Knowledge in the field of technical acoustics is required
• Sound knowledge and experience in the mathematical foundations of machine learning is required
• Sound knowledge in the processing of acoustic or comparable time-dependent signals is required
• Good German and/or English skills required; willingness to acquire the missing
  language skills
• Experience with acoustic measurements is an advantage
• Relevant professional experience in a research environment is an advantage
• Willingness and ability to collaborate in a diverse team is expected

• Work in an internationally visible research environment
• Opportunity for further academic qualification
• Individual professional development and mentoring
• Flexible working hours and the option of partial remote work

Please submit your application, quoting the reference number, including the following documents:

• Cover letter describing your motivation, suitability for the position, and professional interests; in the cover letter, please also briefly explain the extent to which you have already gained experience in technical acoustics, machine learning, and signal processing (e.g., through courses, theses, research projects, or professional activities)
• Curriculum vitae with relevant professional experience, specialist knowledge, and, if applicable, a list of publications
• Copies of certificates and transcripts
  (combined into a single PDF document, max. 5 MB) send your application by email to Prof. Dr.-Ing. Ennes Sarradj ([ta7@akustik.tu-berlin.de).

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To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.