Fwd: [cvnet] Open Positions: 3 PhDs and 1 post-doc in deep learning: focus on brain-inspired inhibition, sparsity and statistical physics (University of Groningen)

[Nils Murrugarra Llerena]

FYI

---------- Forwarded message ---------
From: Nils Murrugarra Llerena <ni...@latinxinai.org>
Date: Thu, Jul 28, 2022 at 12:58 PM
Subject: Fwd: [cvnet] Open Positions: 3 PhDs and 1 post-doc in deep learning: focus on brain-inspired inhibition, sparsity and statistical physics (University of Groningen)
To: Nils Murrugarra Llerena <nine...@gmail.com>

---------- Forwarded message ---------
From: Estefania “etalavera” <estefan...@gmail.com>
Date: Thu, Jul 28, 2022 at 9:50 AM
Subject: Fwd: [cvnet] Open Positions: 3 PhDs and 1 post-doc in deep learning: focus on brain-inspired inhibition, sparsity and statistical physics (University of Groningen)
To: Estefania <estefan...@gmail.com>

Buenas tardes,

George Azzopardi es compañero y amigo que trabaja en la Universidad de Groningen. 

Tiene algunas posiciones disponibles para PhDs y PostDoc, por si conoces a alguien que pueda estar interesad@ :)

Un abrazo!

Estefania

Begin forwarded message:

From: "G. Azzopardi via cvnet" <cv...@lawton.ewind.com>

Subject: [cvnet] Open Positions: 3 PhDs and 1 post-doc in deep learning: focus on brain-inspired inhibition, sparsity and statistical physics (University of Groningen)

Date: 27 July 2022 at 16:00:39 CEST

To: cv...@lawton.ewind.com

Reply-To: "G. Azzopardi" <g.azz...@rug.nl>

Dear all,

The high energy efficiency and generalization abilities in processing sensory information achieved by a mammalian brain are among the gold nuggets of neuromorphic computing. In contrast to conventional super/cluster/grid computing centers which take very large spaces and consume a great deal of energy, a human brain weighs less than 1500g and requires only 20w of power to operate. Emulating these remarkable abilities of the brain represents the pursuit of neuromorphic computing in achieving more with less. 

Sparsity is among the key factors that contribute to high energy efficient processing in the brain. Neuroscientists believe that inhibition is a crucial property that results in sparse and thus highly energy efficient representations. Sparsity and inhibition are the focus of the open positions described below. They will also be investigated with respect to generalisation abilities (i.e. determination of computational models that can generalize beyond the training distribution) and to robustness with respect to adversarial attacks.

Two complementary 4-year PhD positions funded by the CogniGron Center of the University of Groningen:

• 1. Four-year PhD. Sparsity with Brain-inspired Inhibition (Required Background in Computer Science/Artificial Intelligence)
• Main supervisor: Dr. George Azzopardi, Co-supervisors: Prof. Michael Biehl, Dr. Nicola Strisciuglio (University of Twente)

• 2. Four-year PhD. Sparsity with Statistical Physics Analysis (Required Background in Physics)
• Main supervisor: Prof. Michael Biehl , Co-supervisors: Dr. George Azzopardi and Prof. Kerstin Bunte (University of Groningen)

• Interest for the above two positions can be expressed via this form.

Other two positions:

• Two-year post-doc. The selected candidate will be enrolled with the Information Systems group, University of Groningen, and will collaborate with ongoing PhD students on the topic of brain-inspired robust deep architectures. The ideal candidate must have a solid foundation in developing deep learning architectures for vision applications and a proven record of publishing high-quality papers.
• Supervisor: Dr. George Azzopardi (University of Salerno)

• Four-year (double-doctorate) PhD. The selected candidate will be enrolled with the Information Systems group, University of Groningen, and the Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno (Prof. Mario Vento). The candidate would need to spend 2 years at each university, and will focus on investigating how inspiration from the visual system of the brain can be used to develop more robust deep learning architectures with application to computer vision (e.g. face analysis)
• Supervisors: Prof. Mario Vento (University of Salerno) and Dr. George Azzopardi (University of Salerno)

• Interest for the above two positions can be expressed via this form

Best regards,
George
--
Dr. George Azzopardi
Tenure Track Assistant Professor | Information Systems group | Faculty of Science and Engineering | University of Groningen | Nijenborgh 4 (Bernoulliborg) | room 424 | 9747 AG Groningen | The Netherlands | T: +31 (0) 50 363 3934 | W: http://www.cs.rug.nl/~george

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Nils Ever Murrugarra Llerena

Research Scientist - Snap Inc

https://nineil.github.com/