We, the 7 PIs from 5 universities, across 5 European countries, are looking for a total of 13 PhD students. Here you can find the project descriptions. Come join this exciting network!

Vacancies

The objective of SmartNets is to provide high-level training into the functioning of  biological networks to a new generation of early stage researchers, to provide them with the skills necessary for thriving careers in a burgeoning area that underpins innovative technological development across a range of diverse disciplines. This goal will be achieved by a unique combination of “hands-on” research training, non-academic placements (industrial and non-profit organisations) and courses and workshops on both scientific and complementary -so-called “soft”- skills facilitated by the academic-non-academic composition of the consortium. SmartNets brings together neuroscientists, behavioural and cognitive scientists, physicists, computer scientists, and non-profit stakeholders in order to train the next generation of  data scientists that will: 1) develop a fundamental understanding of the relationship between structure and function in biological networks and 2) translate this knowledge into novel technological solutions. ESRs will develop a unique interdisciplinary set of skills that will make them capable of analyzing networks at many levels and for many systems.

NB Note that the Mobility Rule will be applied: PhD students must not have resided or carried out their main activity (work, studies, etc.) in the country of the host for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention, are not taken into account.

Target and pathway discovery in molecular networks

In the nervous system, early stages of information processing are performed by primary sensory pathways where incoming sensory information is encoded topographically to generate neural representations of the sensory world in an activity dependent manner. These sensory maps are products …

Computational Neuroscience
Celikel
Radboud University
Nijmegen
the Netherlands

Role of dendritic nonlinearities in V1 network properties after visual learning

Poirazi Lab (www.dendrites.gr), Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology Hellas (FORTH), Heraklion, GreeceVacancy terms:Full Time, Fixed Term starting from 1st April 2021 for 1 year (renewable for 2 more years)Living allowance: 34,800 euro per …

Computational Neuroscience
Poirazi
University of Crete
Crete
Greece

Role of dendritic nonlinearities in hippocampal network properties after contextual and spatial learning

Poirazi Lab (www.dendrites.gr), Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology Hellas (FORTH), Heraklion, GreeceVacancy terms:Full Time, Fixed Term starting from 1st April 2021 for 1 year (renewable for 2 more years)Living allowance: 34,800 euro per …

Computational Neuroscience
Poirazi
University of Crete
Crete
Greece

How higher-order correlations shape network structure

Many neural circuits shows correlated firing among neurons; these correlations have been shown to be important for the encoding and decoding of sensory information[11]. While most work has addressed correlations between pairs of neurons, recently, an increasing number of experimental …

Computational Neuroscience
Gjorgjieva
MPI Brain Research
Frankfurt
Germany

The role of transient network structures in establishing functional connectivity during development

Generating neural systems that are both flexible and stable is a nontrivial challenge and requires a prolonged period of development when multiple mechanisms are coordinated in a hierarchy of levels and timescales to establish a rich repertoire of computations. Studying …

Computational Neuroscience
Gjorgjieva
MPI Brain Research
Frankfurt
Germany

Whole-brain network dynamics in zebrafish larvae during spontaneous and sensory-driven virtual navigation

Zebrafish larva possesses a combination of assets – small dimensions, brain transparency, genetic tractability – which makes it a unique vertebrate model system to probe brain-scale neuronal dynamics. Using light-sheet microscopy, it is currently possible to monitor the activity of …

Computational Neuroscience
Debrégeas
Sorbonne University
Paris
France

Behavioral characterization of sensory-driven nagivation in zebrafish larvae

Motile animals use sensory cues to navigate towards environments where there are more likely to obtain food, find mates or to avoid predators. Sensory-driven navigation relies on a closed-loop mechanism between motor action and motor-induced sensory inputs. At each instant, …

Behavioral Neuroscience
Debrégeas
Sorbonne University
Paris
France

Collective computation in large animal groups

Despite the fact that social transmission of information is vital to many group-living animals, the organizing principles governing the networks of interaction that give rise to collective properties of animal groups, remain poorly understood. ER6 will employ an integrated empirical …

Behavioral Neuroscience
Couzin
University of Konstanz
Konstanz
Germany

Using immersive Virtual Reality (VR) to determine causal relationships in animal social networks

The application of Virtual Reality (VR) environments allows us to experimentally dissociate social input and responses, opening powerful avenues of inquiry into the dynamics of social influence and the physiological and neural mechanisms of collective behaviour. A key task for …

Behavioral Neuroscience
Couzin
University of Konstanz
Konstanz
Germany

Impact of local topology and local adaptation on network behaviour

The student will start from existing biological network data and network models provided by other partners (F. Zeldenrust, P. Poirazi, G. Debregeas) and investigate the specificity of the relationship between local/global topology and network activity/computation. For this, we will thoroughly evaluate and combine …

Computational Neuroscience
Dambre
Ghent University
Ghent
Belgium

Impact of local topology and local adaptation on network behaviour

The student will study the relationship between the topology and behaviour of networks in the context of adaptation through learning. He/she will focus on random random recurrent network models (e.g., liquid state machines[5], random population networks) that are augmented with …

Machine Learning
Dambre
Ghent University
Ghent
Belgium

Plasticity of network conductivity in somatosensory processing

Cortical networks are not static, but change constantly in response to experience. In particular, in response to strong interventions, networks re-organise themselves so that the neurons representing sensory stimuli that are no longer available get ‘taken over’ by neighbouring areas. …

Computational Neuroscience
Zeldenrust
Radboud University
Nijmegen
the Netherlands

Single neuron non-linearities in somatosensory processing

Rodents use their whiskers (more than other sensory systems) to solve real-world problems like navigation, object localization and texture discrimination. Neurons in the barrel cortex (the part of the rodent brain that processes information from the whiskers), show strong threshold …

Computational Neuroscience
Zeldenrust
Radboud University
Nijmegen
the Netherlands