[ecoop-info] 2 PhD positions in the areas of Model-Driven Engineering, Machine Learning and Cloud Computing starting February 2021

Jean-Marie Mottu jean-marie.mottu at univ-nantes.fr
Mon Dec 28 13:25:26 CET 2020


On behalf of the Lowcomote-ITN, we are pleased to announce the 
recruitment of *two PhD students*. This project is funded by the 
European Union’s Horizon 2020 research & innovation programme under the 
Marie Skłodowska-Curie – ITN, European Training Network programme (Grant 
Agreement n°813884 - https://www.lowcomote.eu/ <https://www.lowcomote.eu/>).


The project is titled /Lowcomote: Training the Next Generation of 
Experts in Scalable Low-Code Engineering Platforms/, and it has *2 PhD 
position*s in the areas of *Model-Driven Engineering, Machine Learning 
and Cloud Computing starting February 2021 for a duration of 36 months.*

Highly competitive and attractive salary is offered (it meets the EU 
Marie Skłodowska-Curie standards), plus mobility and family allowances 
as applicable. Traveling will be part of the programme, substantial 
secondments to partner locations are planned.

The ESR candidates should have a Master degree in Computer Sciences, 
Information Engineering or equivalent.
Main entry point to send applications and to check eligibility criteria 
is the Lowcomote website: https://www.lowcomote.eu/call/ 
<https://www.lowcomote.eu/call/>

Thesis topics:

ESR2 - SCALABLE CLOUD-BASED HETEROGENEOUS MODELLING
Hosted by Uground (Spain)
Details: https://www.lowcomote.eu/esr/02/ <https://www.lowcomote.eu/esr/02/>
Deadline: 31th January 2021


ESR7 - MINING INTERACTION PROCESSES IN LOW-CODE SYSTEM MODELS

Hosted by Johannes Kepler University of Linz (Austria)
Details: https://www.lowcomote.eu/esr/07/ <https://www.lowcomote.eu/esr/07/>

Deadline: 31th January 2021

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-- 
Jean-Marie Mottu, PhD
Associate Professor (Maître de Conférences)

Université de Nantes (IUT de Nantes)
LS2N - UMR CNRS 6004 (NaoMod Team @IMT Atlantique)

IUT de Nantes, 3 Rue Maréchal Joffre, 44000 Nantes, FRANCE
Tel : +33 (0)2 40 30 60 47
Homepage:https://naomod.github.io/



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