21/02/2017
Marie Skłodowska-Curie Actions

MSCA-ITN UTOPIAE: ESR scholarship at INRIA, Towards a New Paradigm for the Control and the Analysis of Experiment Data (ESR3)

This job offer has expired


  • ORGANISATION/COMPANY
    Inria Saclay - Ile-de-France
  • RESEARCH FIELD
    EngineeringAerospace engineering
    EngineeringSimulation engineering
    MathematicsComputational mathematics
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    30/04/2017 12:00 - Europe/Athens
  • LOCATION
    Multiple locations, see work locations below.
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    35
  • OFFER STARTING DATE
    01/10/2017
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / Marie Skłodowska-Curie Actions COFUND
  • MARIE CURIE GRANT AGREEMENT NUMBER
    722734

Computational  Science  aims  at  developing  reliable  and  predictive  numerical  tools,  relying  on  and exploiting the interactions between experiment, computation and theory.  The objective is not only to  numerically  simulate  with  high-fidelity  an  observed  phenomenon,  but  also  to  predict  the  reality in  situations  for  which  the  numerical  tool  has  not  been  specifically  validated  nor  tested.   Reliable numerical predictions require sophisticated physical models as well as a systematic and comprehensive treatment  of  calibration  and  validation  procedures,  including  the  quantification  of  inherent  model uncertainties.

This objective is particularly difficult in the context of large scale flow simulations.  This is due, on the one hand, to the high computational cost of flow simulations using complex numerical models that must account for complex nonlinear phenomenas:  compressibility, discontinuities (compression shocks), turbulence, multi-scale dynamics, etc.  On the other hand, the experimental measurements needed  for  the  calibration  are  delicate  and  expensive  to  perform,  due  mainly  to  the  unsteadiness, turbulent and multiphase nature of the flows.  This limits the amount and accuracy of available measurements for the model calibration, with reduced inference quality and increased model uncertainty as a result.

Solving large scale inverse problems in complex multi-physics systems, with the inference of parameters from noisy data and in presence of model uncertainty, remains a challenging task.  Typically, the  calibration  of  a  physical  model  compares  the  measurements  (provided  by  experimentalists)  to the model predictions (obtained from simulations) in a suitable and objective fashion, accounting for both  data  (measurements)  and  model  (simulations)  errors  and  uncertainties.   Methods  have  been proposed  to  solve  such  inference  problem  (e.g.   in  Bayesian  frameworks),  but  their  computational cost is prohibitive, preventing their direct application to large scale flow inference problems.

The  aim  of  the  ESR  is  to  develop  efficient  and  scalable  methods  to  solve  large  scale  inference problems, quantify the resulting uncertainties in the physical models, and propose new experiments to  optimally  improve  the  predictive  capabilities  of  the  models.  Regarding  the  complexity  issue,  we plan to combine predictions of models with different level of simplifications (multi-fidelity), according to  the  available  computational  resources,  to  construct  a  computationally  manageable  surrogate  of the inference problem.  A long-term objective will to minimize the number of numerical and physical experiments  to  be  performed  in  order  to  calibrate  the  physical  model  with  a  prescribed  level  of confidence.  These  developments  are  also  expected  to  provide  new  perspectives  for  the  simulation-based design and optimization of complex systems. 

The ESR will apply the numerical framework to the analysis of two different experiments :

Benefits

  • Canteen and cafeteria
  • Partial coverage of the transport costs in common
  • Sport equipement

Eligibility criteria

  • Early-Stage Researchers (ESRs) shall, at the time of recruitment by the host organisation, be in  the  first  four  years  (full-time  equivalent  research  experience)  of  their  research  careers  and have not been awarded a doctoral degree.
  • All  researchers  recruited  in  an  ITN  must  be  Early-Stage  Researchers  (ESRs)  and  undertake transnational mobility (including, but not limited to secondments with other UTOPIAE partner institutions, conference attendance, outreach and engagement work and any other appropriate work requiring travel as deemed necessary by their supervisor).
  • Mobility Rule:  at the time of recruitment by the host organisation, researchers must not have resided  or  carried  out  their  main  activity  (work,  studies,  etc.)   in  the  country  of  their  host organisation for more than 12 months in the 3 years immediately prior to the reference date. Compulsory national service and/or short stays such as holidays are not taken into account.

For  all  recruitment,  the  eligibility  of  the  researcher  will  be  determined  at  the  time  of  their  first recruitment  in  the  project.   The  status  of  the  researcher  will  not  evolve  over  the  life-time  of  the project.

Selection process

Applicants  should  submit  a  Curriculum  Vitae,  a  covering  letter  as  a  single  document  detailing the knowledge, skills and experience you think make you the right candidate for the job, two letters of  reference,  a  list  of  your  MSc  courses  and  grades,  copy  of  your  Master’s  thesis  and  preferably  a list of publications.

Applicants should confirm within their covering letter the length of time they have resided in the host country in the last 3 years before the 1st of October 2017.

Additional comments

The  ESR  will  be  supervised  by  P.M.  Congedo  (INRIA)  and  Olivier  Le  Maître  (CNRS),  experts in  uncertainty  quantification  methods  (see http://www.pietrocongedo.altervista.org/ and http://perso.limsi.fr/olm/).

  • Duration of contract: 36 months
  • Monthly gross salary: 39,820.00 per year
  • Starting date: September-November 2017

Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Engineering: Master Degree or equivalent
    Mathematics: Master Degree or equivalent
  • REQUIRED LANGUAGES
    ENGLISH: Excellent

Skills/Qualifications

Candidates are required to have a Master’s degree in engineering, applied mathematics or a related discipline,  and  a  specialization  in  computational  fluid  dynamics,  uncertainty  quantification,  optimization or related fields.  Preferable qualifications for candidates include proven research talent, an excellent command of English, and good academic writing and presentation skills.

Work location(s)
1 position(s) available at
Inria
France
Palaiseau
91120
1, rue Honoré d'Estienne d'Orves
1 position(s) available at
von Karman Institute
Belgium
Rhode-Saint-Genese
1 position(s) available at
Politecnico di Milano
Italy
Milano

EURAXESS offer ID: 183757