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INRIA SIERRA

Dear all,
Apologies for cross-posting. 
We have multiple openings for Interns, PhD students, and Postdoctoral Researchers at the SIERRA Machine Learning Team (Paris, France) which is a joint laboratory between INRIA, the CS Dept. at Ecole Normale Superieure, and CNRS. 
Subject:All the positions will be a part of the ERC Starting Grant (2021) – DYNASTY (Dynamics-Aware Theory of Deep Learning) project, which focuses on various aspects of Deep Learning Theory. The potential topics include (and are not limited to):- Generalization bounds for neural networks- Implicit regularization- Non-convex optimization- Network compression
Candidate Profile: 
– For the Internship positions: Enrollment at a masters/PhD program is required, preferably pure/applied mathematics or statistics.  – For the Phd positions: A masters degree in applied mathematics, statistics, or computer science is required. (A direct PhD after undergrad is not possible).- For the Postdoc positions: PhD degree (and publications) in ML Theory or related fields such as applied mathematics (preferably applied probability, stochastic analysis, operations research), statistics, computer science.
A background on dynamical systems / fractal geometry / heavy-tailed stochastic recursions will be a plus. 
I will not consider candidates that only have an applications background. 
The SIERRA Team:
The researcher will be hosted at the INRIA Paris center, in downtown Paris.

A non­-exhaustive list of topics that are currently investigated by the researchers of the SIERRA team includes:
– Large scale non-­smooth optimization methods.
– Distributed optimization methods (asynchronous stochastic gradient optimization).
– First order-methods.
– Nonconvex optimization.- Kernel methods.  

Application Process / Deadline:
– There is no specific deadline. The applications will be considered on a “first-come-first-serve” basis. – Internships typically take 3-6 months. The timing can be flexible. – In the application, please send a resume, a motivation letter, and at least one reference letter to Umut Simsekli — “umut.simsekli at inria.fr“.  

Best regards,Umut Simsekli–https://www.di.ens.fr/~simsekli/

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ICLR 2022 Challenge of Differential Geometry and Learning

We are co-organizing a computational challenge at the ICLR 2022 workshop of geometry and topology. The goal is to push forward the field of computational differential geometry by asking participants to contribute statistics and learning algorithms on manifolds.

The guidelines of the challenge can be found on its GitHub repository.

The deadline is April 4th, 2022.

Would you know people who could be interested in participating in the challenge? It can be a good opportunity to jump into coding geometry while being rewarded for it: 

- $3500 in prizes, 

- public recognition with an award at ICLR 2022, and 

- co-authorship on the paper summarizing the findings of the challenge. 

Looking forward to your submissions!