The Swiss Data Science Center (SDSC) is a joint venture between EPFL and ETH Zurich. Our mission is to accelerate the adoption of data science and machine learning techniques broadly within academic disciplines of the ETH/EPF Domain, the Swiss academic community at large, and the industrial sector.
The Swiss Data Science Center is a stimulating, startup-like, cross-disciplinary environment in a leading university, that offers opportunities for turning academic research into impactful solutions, with excellent ties to research groups worldwide, both academic and industrial, and has access to state-of-the-art infrastructure and resources.
In this role, you will apply your practical experience in mining and analyzing messy data, your deep understanding of machine learning algorithms, and your willingness to write codes to explore problems and understand data, all while solving challenging real-world problems at a large scale. You will work hand-in-hand with academic experts in domains ranging from personalized health and personalized medicine, earth and environmental science, smart manufacturing (reinforcement learning), computational social science and economics, and digital humanities.
The ideal candidates are researchers who are able to work independently, who are proactive, and take ownership. We are looking for multidisciplinary machine learners with sharp skills in one or more of the following fields: Deep Learning, Bayesian Modeling, Natural Language Processing. We also expect that candidates are proficient in Python/R, Scala, and C/C++.
We look forward to receiving your online application with the following documents:
- Letter of motivation
- Contact details of referees
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about the Swiss Data Science Center (SDSC) can be found on our website https://datascience.ch. Questions regarding the position should be directed to Nina Pupikofer, Tel +41 44 632 80 74 or email firstname.lastname@example.org (no applications).