Vacancy: PhD in data analytics & machine learning for Smart Grids

(01-10-2020)

The “AI for Smart Grids” team, led by prof. Chris Develder at the Internet and Data Lab (IDLab) at Ghent University is looking for a qualified and motivated candidate to pursue a Ph.D. in data analytics and machine learning for smart grid applications.

Job offer

  • PhD position to work on fundamental and applied research projects (4 years)
  • Focus on data science (analytics, modeling, machine learning) for smart grid related applications, as well as scalable/distributed algorithms to coordinate energy consumption and production (demand response, DR)
  • Challenging, creative and constructive environment
  • Unique opportunity to participate in European/national research projects and to cooperate with important ICT-oriented companies
  • Competitive salary

Function

Our research group currently is involved in research projects in the area of smart grids. The focus of our smart grid team in these projects is on data analytics, as well as coordination algorithms for, e.g., demand response. The overall objective of the smart grid applications we want to support is to accommodate large penetration of renewable sources (wind mills, solar panels, etc.) without requiring excessive investments in the power grid infrastructure. This involves characterizing and eventually predicting both power generation (from renewables) and consumption behavior (and its flexibility, e.g., what portion thereof can be shifted in time), using data analytics techniques, constructing generative models, applying machine learning, etc. The next step is to actively control power consumption, e.g., by developing algorithms for energy management systems (to steer power consumption and/or decide what to use local production for, e.g., push into the grid or local storage).

Your role in these projects will be to devise and evaluate cutting edge algorithms, implement them, evaluate them in case studies and report on the results in a well-structured manner. Additionally, depending on the project, this may also involve the design/implementation of software prototypes for simulation and proof-of-concept demonstrations (in lab settings, but also in live field trials). You will perform this work in the context of research projects that will give you the opportunity to interact and collaborate with researchers and engineers from other universities, research institutes and companies. As you will be dealing with several aspects of designing and evaluating systems (mathematical models, machine learning, optimization techniques, software development, simulation, etc.), the function is an excellent opportunity to demonstrate and further improve several of your mathematical and engineering skills. 

Your profile

  • Holder of a M.Sc. degree relevant to the position (e.g., in computer science) with first class performance as demonstrated through outstanding grades, M.Sc. thesis results and/or publications.
  • You have strong analytical skills, you are well organized, you are an excellent communicator, a team player.
  • You have a strong sense of responsibility and are also able to autonomously plan and perform research tasks. You respect the predetermined milestones in research projects.
  • Your English is fluent, both in speaking and writing.
  • Both young graduates and candidates with (industrial) experience are welcome
  • Master computer science, electrical engineering, ICT, or similar disciplines.
  • Knowledge of data analysis, machine learning, optimization techniques (e.g., ILP, heuristics), basic distributed software concepts.
  • A proven experience in software development (e.g., student projects or master thesis with an important software development component), knowledge of Python, Java and/or C/C++. Experience with R and/or Matlab is a plus.

Interested?

Send your CV and motivation letter, including contact details for up to 3 references that we may contact, to chris.develder@ugent.be, indicating “Application: PhD in data analytics & machine learning for smart grids” in the subject.

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