Connectionists: PhD AND POSTDOC POSITIONS IN COMPUTATIONAL NEUROSCIENCE AT ENS, PARIS

[Rava A. da Silveira]

*Several DOCTORAL and POSTDOCTORAL openings in the lab of RAVA AZEREDO DA
SILVEIRA at the Ecole Normale Supérieure, Paris*

We invite applications for several Ph.D. and postdoctoral positions at the
Ecole Normale Supérieure, in Paris. Research questions will be chosen from
a broad range of topics in theoretical/computational neuroscience and
cognitive science (see the description of the lab’s activity, below).

Candidates with backgrounds in mathematics, statistics, artificial
intelligence, physics, computer science, engineering, biology, and
psychology are welcome. Experience with data analysis and proficiency with
numerical methods, in addition to familiarity with neuroscience topics and
mathematical and statistical methods, are desirable. Equally desirable are
a spirit of intellectual adventure, eagerness, and drive.

Doctoral and postdoctoral salaries will be competitive, appreciably higher
than standard French salaries.

The ENS, together with a number of neighboring institutions (College de
France, Institut Curie, ESPCI, Sorbonne Université, and Institut Pasteur),
offers a rich scientific and intellectual environment, with a strong
representation in computational neuroscience and related fields.

*Deadline:*

For full consideration, please apply by 30 January 2020.

*How to apply:*

Please send a letter of motivation, a statement of research interests
limited to two pages, a curriculum vitae including a list of publications,
and any relevant publications to rava at ens.fr, and arrange for three letters
of recommendations to be sent to the same address. In all email
correspondence, please include the mention “APPLICATION-PARIS-PHD” or
“APPLICATION-PARIS-POSTDOC” in the subject header, otherwise the
application will not be considered.

*Description of the lab’s activity:*

Rava Azeredo da Silveira’s lab focuses on a range of topics in theoretical
and computational neuroscience and cognitive science. These topics,
however, are tied together through a central question: How does the brain
represent and manipulate information?

Among the more concrete approaches to this question, the lab analyses and
models neural activity in circuits that can be identified, recorded from,
and perturbed experimentally, such as visual neural circuits in the retina
and the cortex. Establishing links between physiological specificity and
the structure of neural activity yields an understanding of circuits as
building blocks of cerebral information processing. On a more abstract
level, the lab investigates the representation of information in
populations of neurons, from a statistical and algorithmic -- rather than
mechanistic -- point of view, through theories of coding and data analyses.
These studies aim at understanding the statistical nature of
high-dimensional neural activity in different conditions, and how this
serves to encode and process information from the sensory world.

In the context of cognitive studies, the lab investigates mental processes
such as inference, learning, and decision-making, through both theoretical
developments and behavioral experiments. A particular focus is the study of
neural constraints and limitations and, further, their impact on mental
processes. Neural limitations impinge on the structure and variability of
mental representations, which in turn inform the cognitive algorithms that
produce behavior. The lab explores the nature of neural limitations, mental
representations, and cognitive algorithms, and their interrelations.
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