PhD Position in Machine Learning and Simulation-based Analysis for Smart Grids
University of Luxembourg
Esch-sur-Alzette, Luxembourg
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About the SnT

SnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services.

We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent.

We’re looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you’ve come to the right place!

Your Role

As the successful candidate, you will join the Security, Reasoning and Validation (SeRVal) group of the SnT, headed by Prof.

Yves Le Traon. You will contribute more specifically to a partnership project with Creos S.A., the major energy network manager in Luxembourg.

The topic of the project is Secure, Reliable and Predictable Smart Grids and it concerns the application of machine learning and simulation techniques to predict the impact of customers’ consumption on the Luxembourgish smart grid.

The project involves (1) building decision making systems suggesting, based on consumption-related predictions, relevant actions to preserve the stability of the energy network, (2) designing methods to simulate worst-case scenarios (such as incidents) assessing the resilience of the grid to extreme conditions.

The project is held in close collaboration with Creos S.A. and, as one of the successful candidates, you will be expected to program prototype tools showcasing the practical benefits of your research outcomes.

The supervision team you will be working with is :

  • Dr. Maxime Cordy : research scientist
  • Prof. Yves Le Traon : head of SerVal
  • You will be required to perform the following tasks :

  • Carrying out research in the predefined areas
  • Survey the scientific literature in the relevant research domains
  • Disseminating results through scientific publications
  • Communicate with the partner to collect requirements and report results
  • Implement proof-of-concept software tools
  • Your Profile

    Qualification : The candidate should possess an MSc degree (or equivalent) in Computer Science, or in Electrical Engineering with strong programming skills and good knowledge of computer science in general.

    Experience : The ideal candidate should have some knowledge and / or experience in a number of the following topics :

  • Machine learning
  • Simulation-based analysis
  • Multi-objective optimization
  • Smart energy grids
  • Data collection and storage pipeline
  • Strong software development skills are mandatory.

    Language Skills : Fluent written and verbal communication skills in English are required. French is a plus.

    Here’s what awaits you at SnT

    But wait, there’s more!

  • Complete picture of the perks we offer
  • Discover our Partnership Programme
  • Download the brochure : Why choose SnT for your PhD?
  • Students can take advantage of several opportunities for growth and career development, from free language classes to career resources and extracurricular activities.

    In Short

  • Contract Type : Fixed Term Contract
  • Work Hours : Full Time 40.0 Hours per Week
  • Number of positions : 2
  • Location : Kirchberg
  • Employee and student status
  • Start date : between 1st of March and 1st of September 2021, upon agreement.

    Job Reference : UOL03746

    Further Information

    Application should include :

  • Full CV, including list of publications and name (and email address, etc) of three referees
  • Transcript of all modules and results from university-level courses taken
  • Research statement and topics of particular interest to the candidate (300 words)
  • Motivation letter
  • All qualified individuals are encouraged

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