Your responsibilities
The successful candidates will join a data science task force at the NCCR’s headquarters in Zurich in co-affiliation with the University of Zurich’s Technology Platform LiRI (Linguistic Research Infrastructure). The task force will work intensively with researchers across the entire network of the NCCR and so the members of the task force are expected to also spend time in the various labs of the network (conditions permitting). The task force will actively collaborate with data science platforms at the ETH Zurich and EPF Lausanne (e.g. the Swiss Data Science Centre) as well as with partners in industry (e.g. the Google Research Natural Language Processing Group in Zurich).
Your profile
The ideal candidates have a PhD degree in a relevant discipline such as speech recognition, sound separation, computational neuroscience, neuroinformatics, or natural language processing. They are knowledgeable in problem settings in the domains relevant to the NCCR and are well versed with machine learning techniques including deep learning and reinforcement learning. They are experienced in developing efficient solutions in both small and big data settings.
The NCCR places great emphasis on teamwork and on multidisciplinary perspectives. Excellent communication and collaboration skills are essential.
What we offer
We offer varied and interesting work in an inspiring and socially relevant environment. Diversity and inclusion are important to us. The NCCR places great emphasis on gender balance; we particularly encourage women to apply.
Start of employment
Applications should include
- a cover letter stating your motivation and vision for the field,
- a CV with publication list,
- a copy of the highest degree,
- and the names of three references.
Review of applications starts November 1 and applications are accepted until the position is filled. Please submit your application through the website of the University of Zurich as a single PDF labelled ‘MachineLearning-YourSurname.pdf. Questions can be addressed to Prof. Richard Hahnloser.
