You are here : Home > News > Call for applications: 13 PhD trainings funded by the H2020 program NUMERICS and INSTN

Highlight | Europe

Call for applications: 13 PhD trainings funded by the H2020 program NUMERICS and INSTN


Within the international program NUMERICS, launched by the CEA in the fields of numerical simulation and scientific computing and supported by the EU Horizon 2020, the Frédéric Joliot Institute for Life Sciences obtains the label of 13 research projects for the recruitment of talented international students. Applications must be sent by April 30, 2020.

Published on 18 February 2020

NUMERICS is a project supported by the EU Framework Program for Research and Innovation Horizon 2020. It aims to fund PhD students conducting research at the CEA in the field of simulation, modelling, big data and artificial intelligence. For the last funding period 2020-2023, thirteen topics have been selected for the Joliot Institute. European funding (50%) will be completed by INSTN from its PhD program budget so that the laureates can be offered a PhD thesis contract fully paid by CEA.

Master students, if you are interested in one of the subjects (see below), you must apply before April 30, 2020. Before applying, you should verify that you meet the following criteria : you must not have resided or carried out your main activity in France more than 12 months over the three years prior to the call deadline (mobililty condition).

For further information on how to apply: 
https://numerics.cea.fr/Pages/Numerics/Apply/How-to-apply.aspx

List of projects selected for the Institute 

  • I2BC (Institute for integrative biology of the cell):

    • SL-DRF-20-0379 - Computational integration and modelling of DNA repair kinetics in eukaryotes. (supervisor Julie Soutourina)
    • SL-DRF-20-0922 - Combinations of Multiscale Molecular Dynamics simulations and experiments for studying confined proteins in reverse micelles: Influences of the structural parameters affecting their stabilities. (supervisor Stéphane Abel)
    • SL-DRF-20-0923 - Small angle X ray scattering reconstruction from coarse grained model and atomistic models of proteins. (supervisor Massimo Marchi)
    • SL-DRF-20-0954 - Modelling of the interaction between proteins and nanoparticles: a machine learning and molecular simulation mixed approach. (supervisor Yves Boulard)
  • DMTS (Medicines and Healthcare Technologies Department):

    • SL-DRF-20-0935 - Machine learning guided artificial evolution to counter antibiotic resistance. (supervisor Loïc Martin)
    • SL-DRF-20-0963 - Improving phylopeptidomics by supervised classifier training with massive data on biological models for better organism quantification and functional metaproteomics of microbiota. (supervisor Jean Armengaud)
  • NeuroSpin:

    • SL-DRF-20-0360 - Application of machine learning to the comparison of Alzheimer Disease with its analogue in chimps. (supervisor Jean-François Mangin)
    • SL-DRF-20-0816 - Deep learning for the joint optimization of accelerated sampling and reconstruction schemes for high-resolution brain MRI at 7 and 11.7 Tesla. (supervisor Philippe Ciuciu)
    • SL-DRF-20-0939 - Mapping brain development in the newborn: analyses of large database in multi-modal and multi-scale imaging and modeling. (supervisor Jessica Dubois)
    • SL-DRF-20-0946 - The algorithmic mind in time: investigating temporal cognitive maps of the human brain with generative models. (supervisor Virginie van Wassenhove)
    • SL-DRF-20-0958 - MRI-based unsupervised machine learning (clustering) of psychiatric conditions. (supervisor Josselin Houenou)
    • SL-DRF-20-0959 - Simulation of the neural effects of electrical deep brain stimulation: from experimental data to computational models. (supervisor Béchir Jarraya)
    • SL-DRF-20-0960 - Development of AI methods for deep learning of the MRI signature of the cortex cytoarchitecture with diffusion MRI. (supervisor Cyril Poupon)


Top page