Working Student all genders Deep Learning for Audio Signal Processing
Working Student all genders Deep Learning for Audio Signal Processing
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Job Description
You are interested in combining research and practices and would like to adapt competences in the field of Machine Learning Then have a look at our offer!
What you will do
You will stay up to date with the latest research and read scientific papers
You will implement and experiment with stateofthe art research topics
You will develop interactive demos to showcase research results
You will explore the feasibility of integrating research results into realworld applications
What you bring to the table
You are currently studying Electrical Engineering Computer Science Mathematics Physics or a related field
You are experienced in digital signal processing
You have already worked with TensorFlow/PyTorch
You have a good understanding of linear algebra statistics and probability theory
You are interested in current developments of discriminative and generative AI for Audio/Video processing domain
You show initiative and work independently
You speak English fluently
Optional: You have worked with Python before
What you can expect
Flexible working hours
Open and friendly team work
Varied tasks with room for creativity
Exciting seminars and events
Networking with scientists
Active contribution in applied research
Interesting and innovative projects
Weekly working hours are determined by agreement. You can start from now on (as a student assistant from 15 up to 20 hours a week. You can reduce your hours before exams and increase them during semester breaks. You can flexibly determine the working days. After your studies there may be an opportunity to work with us full or part time.
We would be happy to offer you the opportunity to write a masters thesis in cooperation with us in the abovementioned subject area. The thesis will be assigned and carried out in accordance with the rules of your university. For this reason please discuss the thesis with a professor who can advise you over the course of the project.
We value and promote the diversity of our employees skills and therefore welcome all applications regardless of age gender nationality ethnic and social origin religion ideology disability sexual orientation and identity.
Ready for Change
Do you have questions about the position or the application process Our recruiter Nina Wrlein is there for you:
Employment Type
Part-Time
