The University of Geneva seeks one postdoc in computational neuroscience to investigate the relation between information transfer at synapses and in neural networks, and concomitant energy consumption. The starting date is May 2017. This position is fully funded by the Swiss National Science Foundation for 24 months. Initial appointment is for one year. Research will be conducted in the medical physics group of the physics section at the University of Geneva, under the supervision of Prof. Renaud Jolivet. * Summary Information transmission in the brain is energetically expensive, yet has to satisfy demands of speed and signal-to-noise reliability. We have recently shown that the strong retinogeniculate synapse relaying information from the retina to the thalamus resolves these competing constraints by maximizing energetic efficiency when transferring information. In their physiological state, these synapses are not set to transmit the maximum amount of information possible: information transmission increases when larger excitatory postsynaptic currents (EPSCs) are injected into the postsynaptic thalamic neuron. However, EPSCs that are larger or smaller than physiological EPSCs decrease the information transmitted per energy used. The physiological EPSC size therefore maximizes energy efficiency rather than pure information transfer across the synapse. In other words, the retinogeniculate synapse trades information for energy savings (http://dx.doi.org/10.1016/j.cub.2015.10.063; http://dx.doi.org/10.1016/j.neuron.2012.08.019). These findings suggest maximization of information transmission per energy used as a design principle in the brain. However, it is unclear how broadly this principle applies. Whether energy efficiency at excitatory synapses is a special property of strong relay synapses, or a more general principle also governing synaptic inputs that contribute more weakly to determining the output of the postsynaptic cell is an open question. These findings also raise the question of what mechanisms are in effect in order to achieve energetic efficiency of information transfer at synapses. This project will address these questions using information theory and simulations of biologically validated neuron models. Applicants must imperatively be self-sufficient programmers (MATLAB preferred) and have a strong background in computational neuroscience. They should be familiar with several of the following topics: information theory, Hodgkin-Huxley models, the NEURON simulation environment, signal processing, models of synaptic plasticity, models of neural networks. Please contact renaud.jolivet@unige.ch<mailto:renaud.jolivet@unige.ch> for additional information. * About the University of Geneva (UNIGE) UNIGE is a generalist French-speaking university located in Geneva, Switzerland. The QS World University Rankings 2016 and Times Higher Education World University Rankings 2016/17 respectively rank UNIGE as 95th and 131st worldwide. It ranks 41st worldwide for science (Shanghai Academic Ranking of World Universities in Natural Sciences and Mathematics 2016). It is Switzerland’s second largest university with more than 17000 students of 150 different nationalities and about 4000 researchers of 113 nationalities, who study and work in 9 different faculties. UNIGE trains a large number of PhD students and postdocs in neuroscience. The various research and teaching activities are listed at http://neurocenter.unige.ch/ and at https://www.unil.ch/ln/en/home.html. UNIGE is also developing with other institutions a new campus in Geneva (http://www.campusbiotech.ch/en/), focusing heavily on neuroscience and translational research. Geneva is at the heart of a conurbation with more than 1.25 million inhabitants. It is a global city, a financial center, and worldwide center for diplomacy and research. It has one of the highest quality of life in the world. It offers varied cultural activities and outdoor opportunities being located at one extremity of Lake Geneva, one of the largest lakes in Europe, on the western doorstep of the Alps. The University of Geneva offers competitive salaries and conditions at all levels in a young, dynamic, and multicultural environment. It is an equal opportunity employer and women are encouraged to apply. The official language of the laboratory is English. * How to apply Please send an e-mail to renaud.jolivet@unige.ch<mailto:renaud.jolivet@unige.ch> with your resume, list of publications, a one-page statement describing your research interests and career plan, and the names of at least three references. — Prof. Renaud Jolivet CERN, Experimental Physics Department & University of Geneva, Physics Section +41 22 767 24 70 (CERN) +41 22 379 62 75 (UNIGE) +41 79 830 21 29 (mobile) renaud.blaise.jolivet@cern.ch<mailto:renaud.blaise.jolivet@cern.ch> https://sites.google.com/site/renaudjolivet/