PhD position Neural network model of memory engram consolidation via astrocyte-neuron interaction

Updated: 3 months ago
Job Type: FullTime
Deadline: 20 May 2021

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European Commission › EURAXESS › Jobs & Funding › PhD position Neural network model of memory engram consolidation via astrocyte-neuron interaction
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24/03/2021
PhD position Neural network model of memory engram consolidation via astrocyte-neuron interaction
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PhD position Neural network model of memory engram consolidation via astrocyte-neuron interaction
Application Deadline: 20/05/2021 12:00 - Europe/Athens
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Company
University of Trento

  • WEBSITE
    https://www.unitn.it/drphys/en/119/admission

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  • ORGANISATION/COMPANY
    University of Trento

  • DEPARTMENT
    Department of Physics - Nanoscience Laboratory

  • ORGANISATION TYPE
    Higher Education Institute

  • WEBSITE
    http://nanolab.physics.unitn.it/

  • E-MAIL
    lorenzo.pavesi@unitn.it

  • COUNTRY
    Italy

  • CITY
    Povo

  • STATE/PROVINCE
    TRENTO

  • POSTAL CODE
    38123

  • STREET
    via Sommarive 14

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  • ORGANISATION/COMPANY
    University of Trento

  • RESEARCH FIELD
    PhysicsComputational physics

  • RESEARCHER PROFILE
    First Stage Researcher (R1)

  • APPLICATION DEADLINE
    20/05/2021 12:00 - Europe/Athens


  • LOCATION
    Italy › Povo

  • TYPE OF CONTRACT
    Temporary

  • JOB STATUS
    Full-time

  • HOURS PER WEEK
    40

  • OFFER STARTING DATE
    01/11/2021

  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / ERC

  • REFERENCE NUMBER
    788793

OFFER DESCRIPTION

The behavior of complex biological networks can be locally reproduced by fundamental physics laws and globally by statistical properties. The aim of this project is to develop a computational model of the formation of memory engrams. By leveraging on the experimental biological data collected within the BACKUP - ERC project and the computational expertise of the Statistical and Biological Physics Group, the project will model the neuron and the astrocyte networks interaction to consolidate a memory engram. In the context of the available biological data by the BACKUP project, we propose to generate computational models to abstract out as many biological details as possible while capturing functionality and maintaining a faithful representation of neuronastrocytes interaction in memory consolidation The PhD topic is about the development of statistical and machine learning models to understand the interplay among neurons and astrocytes networks in engram formation. The PhD student will collaborate with the proponent groups to: 1. Acquire neuronal activity maps via light activated neuron-astrocyte networks within optical microscope imaging using optogenetics and electrophysiological techniques. 2. Develop a model based on statistical mechanics and machine learning methods to describe the acquired experimental data. 3. Provide simulations to plan new biological experiments to verify the model predictions. This PhD will be part of the ERC-funded BACKUP project (P.I. Prof. Lorenzo Pavesi, Dept. of Physics). More info at https://r1.unitn.it/back-up/


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Offer Requirements
Skills/Qualifications

We are seeking for a highly-motivated and passionate student, with a strong attitude to work in a collaborative and interdisciplinary team, and with a background in computational physics.


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1 position(s) available at
University of Trento
Italy
TRENTO
Povo
38123
via Sommarive 14
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EURAXESS offer ID: 619442


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