3-year PhD position in Computational Models of Analogy Making in Natural Language (IRIT and University of Toulouse, France)
We invite applications for a fully funded PhD position for 3 years at the IRIT laboratory and the University of Toulouse, Paul Sabatier, France, in the context of the recently funded project AT2TA on Analogy Making.
Analogy Making is a remarkable cognitive capability during which similarities and differences between two parallel situations are exploited in order to draw a common "essence" allowing us thus to categorize an object or a particular situation to a preexisting concept or create a new one. Reasoning by analogy allows us thus to transfer our understanding of a previous situation to a new one and appropriately adapt it. It has been argued that analogy making lies at the core of cognition (Hofstadter 2001) and has recently drawn the attention of Deep Learning pioneers (Chollet 2017, LeCun 2022).
In Natural Language Processing analogies usually take the form of a quadruplet a:b :: c:d traditionally expressed as "a is to b as c is to d" (for example, Paris is to France as Berlin is to Germany). Most of the extant work considers a, b, c, d as word embeddings and then relies on geometrical properties of those embedding in a higher dimensional space in order to recognise a quadruplet as an analogy or to generate a d such that a:b :: c:d forms analogy given a, b and c. Despite the importance of analogies, most works in NLP do not consider analogies between sentences and do not concentrate on the underlying latent relations that form the common essence between pairs (a,b) and (c,d). The successful PhD candidate will work on computational models which can identify analogies between sentences or even bigger chunks of text with a particular focus on the identification of common latent relations which are also an essential part for an explainable AI.
The successful candidate should hold a Master's degree in computational linguistics or computer science or cognitive science and has prior experience in word embedding models or deep learning approaches in general. The candidate should have strong programming skills and expertise in machine learning. The position is affiliated with the IRIT laboratory at Toulouse and there will be frequent interactions with researchers at the Loria laboratory in Nancy in the context of the AT2TA project.
Applications will be considered until the position is filled, but applicants are encouraged to apply as early as possible since applications will be considered at the moment of reception. Applications, in English or French, should include a detailed CV, a letter of motivation and at least two recommendation letters. Applications should be sent to Stergos Afantenos (stergos.afantenos at irit.fr).
More information can be found here: https://cloud.irit.fr/index.php/s/OpwyvCBzadRFKxY