*Post-Doc position in Computational Neuroscience on causal learning * *Institut des Systèmes Intelligents et de Robotique, Paris (UMR7222)* *Groupe d'Analyse et de Théorie Economique, Lyon (UMR 5824)* *General Information* Workplace: LYON/PARIS Employer: CNRS Type of contract: FTC Scientist Contract Period: 18 or 24 months Expected date of employment: 2 September 2019 Proportion of work: Full time Remuneration: between 2643 and 3766 Euros gross monthly salary depending on the candidate’s experience Desired level of education: PhD Experience required: indifferent *Missions*: The objective of our project is to investigate the neural and computational bases of causal learning. In particular, we will focus on causal learning in the context of goal-directed instrumental behaviors, which rely on learning rules determined by the contingency//between actions and outcomes. In order to unravel the neural and computational bases of action-outcome causal learning, we need to lift two key barriers. The first barrier is the lack of neurocomputational models that formalise the above-mentioned theoretical framework to make precise predictions about the underlying neural computations. The second barrier is the lack of clear understanding of the brain network dynamics supporting action-outcome causal learning. *Activities: * The selected candidate will contribute to lift the first barrier, by developing neurocomputational models that: i) formalise internal representations and computations predicted by causal learning theories (/rational /and /Bayesian /frameworks); ii) make predictions about the dynamics of neural activity (i.e., neurobiological plausibility) and fit single-participant behavioral patterns (i.e., computational flexibility). Among the possible learning models, two seem to provide the adequate theoretical and computational framework: Active Inference and Reinforcement learning. The former is a Bayesian approach postulating that human behaviour can be reduced to the minimization of variational free energy, which is an upper bound on Shannon surprise (Friston, 2010). The latter provides a complementary view and formalizes human behavior as a process that aims at maximizing cumulative (extrinsic or intrinsic) reward (Sutton & Barto, 1998). The selected candidate will help designing a new experimental protocol to test the specific predictions of these computational frameworks, and compare them with Bayesian model comparison methods. The experiment will involve human subjects and be realized with the facilities of the GATE (Experimental Economics) laboratory in Lyon, France. Then we will derive a computational model which best accounts for human behavior while they learn causalities, and make model-driven predictions for a new task involving brain imaging (fMRI, MEG, SEEG) performed in humans by partners of the project. *Skills*: Applicants should be highly motivated, have a PhD in computational neuroscience, physics, computer science, or related fields, with a track record of publications. Confirmed experience in computational modelling and programming skills are mandatory. Preference will be given to applicants with previous experience in causal learning models in neurosciences. *Work context*: We have obtained funding from the French Agence Nationale de la Recherche for 4 years project aiming at lifting the previously mentioned two barriers. The project involves both theoreticians (Mateus Joffily in GATE, Lyon, France; Mehdi Khamassi in ISIR, Paris, France; David Lagnado in UCL, London, UK) and experimentalists (Andrea Brovelli in INT, Marseille, France; Julien Bastin in GIN, Grenoble, France). This 2 years post-doctoral research position is available to work at the interface between two laboratories: the GATE in Lyon and the ISIR in Paris. *Additional Information*: The position is available immediately and applications will be reviewed until the position is filled. The selected candidate will be hired for a period of 18 to 24 months with a salary corresponding to the level of research scientist according to the standards of the National Center of Scientific research (CNRS). Salary will include social security, health and retirement benefits. Applications should include: 1) a cover letter briefly describing experience, motivation and skills adapted for the position, as well as research interests; 2) complete CV and publication list; and 3) two letters of reference that should be sent directly to us by the evaluators. Notification of interest should be sent to both Mehdi Khamasi (mehdi.khamassi@upmc.fr <mailto:mehdi.khamassi@upmc.fr>) and Mateus Joffily (joffily@gate.cnrs.fr <mailto:joffily@gate.cnrs.fr>). Applications shall be done through the following website: https://emploi.cnrs.fr/Offres/CDD/UMR5824-TAIDAO-009/Default.aspx?lang=EN. -- Mehdi Khamassi, PhD, HDR Permanent research scientist (CRCN) at the Centre National de la Recherche Scientifique, Institute of Intelligent Systems and Robotics Sorbonne Université, Paris, France http://www.isir.upmc.fr Director of Studies for the Cogmaster program Ecole Normale Supérieure, EHESS, Univ. Paris Descartes http://sapience.dec.ens.fr/cogmaster/www/ Visiting Researcher at the Institute of Communication and Computer Systems National Technical University of Athens, Greece https://www.iccs.gr/en/?noredirect=en_US Visiting Researcher at the Department of Experimental Psychology University of Oxford, UK https://www.psy.ox.ac.uk Main contact details: Mehdi Khamassi Sorbonne Université, Campus Pierre et Marie Curie - ISIR - BC 173 4 place Jussieu, 75005 Paris, France tel: + 33 1 44 27 28 85 cell: +33 6 50 76 44 92 email: mehdi.khamassi@upmc.fr http://people.isir.upmc.fr/khamassi