We have 3 open positions for research fellows in Computational Neuroscience, bio-inspired Robotics and Computer Science (GPU accelerated computing).
The positions are part of the new Brains-on-Board project (http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/P006094/1), which is a multi-university collaboration aiming to create robotic controllers that will enable autonomous robots with the navigational and learning abilities of a honeybee.
The project involves five research groups at the University of Sheffield, Queen Mary University, London, and the University of Sussex performing research whose goal is biomimetic robot control and which will combine autonomous robotics, computational neuroscience, accelerated neural network simulations on GPU architectures and insect neuroscience and behaviour.
In Sussex we are seeking to employ a team of 3 research fellows for initially 2 years, with possible extension up to 5 years.
We envisage the fellows to start in January 2017.
RF 1 (ref 1388) in bio-inspired robotics, will develop insect-derived models of navigation and apply them to autonomous robots.
The work will include refining and developing models of insect navigation and testing them on robotic platforms ranging from the Sussex Gantry robot through wheeled robots to autonomous aerial vehicles.
A successful candidate will have a keen interest in the interface of computational biology and bio-inspired robotics and a proven track record in working in this area.
RF 2 (ref 1389) in Computational Neuroscience, will work on models of associative learning, multimodal integration and decision making in insects.
The work will include formulating neuronal network models of the mushroom bodies, central complex and motor areas of the bee brain constrained by experimental data. The models will then be employed and tested on robotic platforms, including wheeled robots and aerial vehicles.
A successful candidate will have a keen interest in computational neuroscience and experience with computational modelling.
RF 3 (ref 1390) in Computer Science, working on GPU accelerated simulation of brain models and brain-inspired robot controllers, building on our GeNN meta-compiler and the SpineCreator/SpineML API to GeNN.
The work will include developing methods for model- and hardware-aware GPU-accelerated simulations methods that will allow us to efficiently simulate both large-scale models in Computational Neuroscience on super-computers and bio-inspired robotic controllers on embedded systems GPU accelerators.
A successful candidate will have proven skills in complex software development with a focus on scientific computing.
All RFs will work together on the project within Sussex and in the larger Brains-On-Board team.
We encourage applicants to apply for multiple positions if they are interested and feel qualified. Please indicate any preferences when applying for multiple positions.
In order to apply got to http://www.sussex.ac.uk/aboutus/jobs/1388-1389-1390 where you can find further details and the application form.
The closing date is 1 December 2016.
For informal enquiries, please contact Prof Thomas Nowotny (t.nowotny(a)sussex.ac.uk<mailto:t.nowotny@sussex.ac.uk>) or Dr Andy Philippides (andrewop(a)sussex.ac.uk<mailto:andrewop@sussex.ac.uk>).
With kind regards,
Thomas
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Prof Thomas Nowotny
Director of Research and Knowledge Exchange
School of Engineering and Informatics
University of Sussex
Falmer, Brighton BN1 9QJ, UK
Phone: +441273678593
FAX: +441273877873
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PhD position in the Blue Brain Project - Department of In Silico Neuroscience
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Project title: Principles of biophysical structural plasticity in the neocortex
Supervisors: Prof. Henry Markram, Dr. Eilif Muller
Keywords: simulation, neocortex, plasticity, network reorganization,
assemblies, coding, dendrites, calcium, NMDA
Project description:
During our lifetimes, our brains undergo continuous changes as a
consequence of our experiences. Synaptic plasticity—the biological
process by which brain activity leads to long-term changes in synaptic
connections—is thought to be central to learning and memory. However,
little is known about how this process shapes the specialization of
biological neural networks, such as the neocortex. The objective of the
present work will be to devise, implement and study data-driven
biophysical models of synaptic and structural plasticity for the
formation of functional neocortical networks. This project will
leverage the Blue Brain Project data-driven reconstruction of a
neocortical microcircuit [1], and augment it with data-driven
biophysical calcium-based models of synaptic and structural
plasticity. The specific objective of this PhD project will be to
implement and constrain models of structural plasticity, and study the
formation of assemblies, and emergent structure-function relationships
in the presence of structured input. The prospective student will join
an ongoing collaboration including international experts in biophysical
modeling of plasticity and dendrites, topological analysis of network
structure, and optimization of neural simulations for large
supercomputers. A significant allocation of computing time on a large
HPC system will be at the disposal of this project.
[1] Markram, H., Muller, E., Ramaswamy, S., Reimann, M. et al.
Reconstruction and Simulation of Neocortical Microcircuitry. Cell
163:2, 456-495 (2015).
Key external collaborators: Dr. Michael Graupner (CNRS, Université
Paris Descartes), Prof. Idan Segev (Hebrew University Jerusalem)
This project is offered in the context of the EPFL Doctoral School in
Neuroscience (EDNE). Please visit http://phd.epfl.ch/neuroscience-openings
for further details, and information on how to apply.
Application Deadline: Nov 15th, 2016.
For further details on the project contact:
Dr. Eilif Muller <eilif.mueller(a)epfl.ch>
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Dr. Eilif Muller
Section Manager - In Silico Neuroscience - Experimentation
EPFL - Blue Brain Project
Biotech Campus
Chemin des Mines 9
1202 Geneva
Switzerland
Tel: +41 21 693 0698
Fax: +41 21 693 5350
www: http://bluebrain.epfl.ch/page-77926-en.html
www: http://neuralensemble.org/people/eilifmuller
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(a)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(a)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(a)cern.ch<mailto:renaud.blaise.jolivet@cern.ch>
https://sites.google.com/site/renaudjolivet/
