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M/W PhD proposal in bioinformatics and/or applied mathematics. Application of artificial intelligence to study development and evolution of drawings in hominids.

This offer is available in the following languages:
Français - Anglais

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General information

Reference : UMR7178-REGSOM-045
Workplace : STRASBOURG
Date of publication : Wednesday, May 06, 2020
Scientific Responsible name : SUEUR Cédric
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2020
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

Thesis summary: This PhD project explores the appearance and learning of drawing in hominids through novel mathematical indices and artificial intelligence (deep learning). Some of these indices are spatial (outlines, use of space), others are temporal (behavioural sequences), and others are based on the use of colour. These indices then allow us to compare drawings from different categories of participants (children 2 to 10 years old, adults who are experts and naive in drawing, but also great apes). This comparative approach leads us to a better understanding of the ontogeny and learning of drawing in humans, but also its phylogeny in hominids. This PhD project is interdisciplinary since it uses behavioural biology (ethology), comparative psychology (human and non-human), mathematics (fractals in particular) and computer science (machine learning). Human participants (children and adults) are tested in Strasbourg. To work with great apes, we collaborate with Japanese primatologists. The PhD student will be in charge of developing deep learning algorithms to show differences between drawings at different levels: 1. interspecific, in particular orangutans, chimpanzees and humans; 2. in humansn as a function of age; 3. Also in humans, as a function of expertise (expert vs. naive).
Scientific fields and scientific themes: Ethology, Anthropology, Comparative Psychology, Artificial Intelligence, Machine Learning, Bioinformatics, Applied Mathematics.

Work Context

The PhD student will be supervised by Marie Pelé and Cédric Sueur at the IPHC (Institut Pluridisciplinaire Hubert Curien, part of CNRS and Université de Strasbourg). IPHC is a success about interdisciplinary where teams of different scientific domains (ecology, physiology, chemistry, physics) develop high-level integrative programmes with pioneer metrology. Cédric Sueur is expert in ethology at the Department of Ecology, Physiology and Ecology. He uses mathematics and modelling for many years in order to better understand animal and human behaviours. Marie Pelé is primatologist at IPHC-DEPE, expert in comparative cognition and used to work experimentally with apes and humans. Both supervise Lison Martinet's PhD thesis about drawings. With Jérôme Pansanel, research engineer at the IPHC and director of France Grilles, they will develop machine learning and fractal indices to analyse drawings. Satoshi Hirata and Tetsuro Matsuzawa are primatologists and experts on cognition in chimpanzees. Thanks to them, drawings in great apes will be collected.

Constraints and risks

Doctoral School: The PhD student will be enrolled at ED414, Doctoral School of Life and Health Sciences, at Strasbourg University.

Required skills:
—Master diploma or engineer in bioinformatics or mathematics
—Knowledge about mathematics applied to biology, fractals and artificial intelligence (artificial neural networks)
—Knowledge about programming languages as R, Python or C++.
—Language skills in English and French.
—Writing skills, ability to formulate/work on a scientific project
—Ability to work in a team
—Ability to work independently, organisational ability and ability to account for one's own actions
—Ability to work to foreign countries.

Additional Information

Documents to be provided
Applications must include a detailed CV; at least two references (people who may be contacted); a cover letter of one page; the master thesis, grades for the Masters 1 or 2 or the engineering degree.

Closing date for sending applications: 15/07/2020

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