导师简介
Fanny Yang is an Assistant Professor in the Computer Science Department (D-INFK) at ETH Zurich. Previously she was a postdoctoral Scholar at Stanford University working with John Duchi and Percy Liang and a Junior Fellow at the Institute for Theoretical Studies at ETH Zurich working with Nicolai Meinshausen. Before that, she was a PhD student at the EECS department of UC Berkeley advised by Martin Wainwright.
She is generally interested in theoretically understanding and developing tools in machine learning and statistics that work well. Currently she is particularly curious about gaining theoretical understanding for the generalization properties of overparameterized models for high-dimensional data (motivated by neural networks) as well as a plethora of questions related to obtaining more trustworthy ML models, specifically distributional robustness, domain generalization and interpretability.
Website：
http://www.fanny-yang.de/
The position will be within the Statistical Machine Learning research group in the Department of Computer Science at the ETH Zurich, led by Prof. Fanny Yang.
Thematically, possible topics may be in the intersection of high-dimensional and non-parametric statistics, theory for overparameterized models, frequentist inference, and theory for domain generalization and distribution shifts. Related areas of interest can also be discussed. For a flavor of recent work in our group, please visit:
http://www.fanny-yang.de/group.html
Important is a combined passion for solving relevant data science problems in practice with the curiosity to gain a deep theoretical understanding of modern phenomena in data science.
申请要求
1. an excellent completed (by the start date) Master's degree preferably in Statistics, Mathematics or Data Science, but also accepting applications from Electrical Engineering, Computer Science or other strongly mathematically oriented programs;
2. research experience in the field of machine learning (at least one project on a theoretical ML topic);
3. proven software engineering skills in Python or similar;
4. fluency in English;
5. You should be highly self-motivated, be interested in tackling challenging research problems, have organizational skills, be open-minded, and have scientific leadership potential.
1. An interesting, varied and challenging position within a young, international, and interdisciplinary team located at the main campus of ETH Zurich.
2. The position is paid at the highest rate Salary level 5 and is guaranteed for a duration of 4 years.
To apply, please upload a complete application package (note that applications without at least two references will not be considered) to:
https://www.lehrbetrieb.ethz.ch/BewDokFrontend/login.view?lang=en
And send an email with a CV and transcripts to Prof. Fanny Yang (fan.yang@inf.ethz.ch).
