Five open PhD positions at the University of Geneva in the field of deep machine learning

The Machine Learning Group at the University of Geneva, headed by Prof. Francois Fleuret, has five open PhD positions in the field of deep machine learning, with a particular interest for reinforcement learning, interpretability, density models in large dimension, anomaly detection, and computational reduction.

These positions are funded by the Swiss National Science Foundation and the University of Geneva, and salaries are highly competitive.

Ideal starting time is Fall 2020 but can be delayed until early 2021.

Applicants must be seasoned programmers used to modern development tools and machine learning frameworks (e.g. git, numpy, PyTorch, TensorFlow, JAX), and have a strong background in mathematics, in particular in probabilities, signal processing, optimization, and algorithmic.

Application should be done on-line by filling this form.

Founded in 1559, the University of Geneva is the third largest university in Switzerland by number of students, and ranked second according to the Shanghai Ranking of World Universities 2019.

The city of Geneva is centrally located in Europe, host of numerous international organizations (e.g. UN, WHO, WIPO, WTO, ICRC, CERN), and provides an ideal environment for foreign students and researchers.

Some remarks regarding applications

I get a very large number of requests and applications for internships, PhDs, and post-docs, and it is unfortunately impossible to answer to them all.

When I do have open positions, I advertise them on the connectionists mailing list and the Machine Learning News Google Group, and they appear on my web page. Any formal application must be done through this online form.

If you want information regarding future openings, please send me a short email—less than ten lines—stating: what schools and universities you attended or attend, why you are interested in my research group, what time period you are interested in, and if you would already have funding.

I prefer by far conciseness and precision to verbosity and deference. The worst you can do is to send me a wall of text that you use to carpet-bomb dozens of potential places.