Description

Research challenge:
Current state-of-the-art approaches for probabilistic forecasting are either incapable of considering time-correlation, or make use of (too) rough assumptions about the Gaussian character of the involved stochastic disturbances. The research challenge is to develop performant and accurate probabilistic forecasting methods that overcome these drawbacks and use novel stochastic Machine Learning (ML) techniques to capture time-correlation without resorting to approximations, tackling the difficulties of scenario-based forecasting. Such ML techniques may include Deep Learning Networks, Neural Processes, Approximate Bayesian Inference, Hybrid Models etc.

 

Approach:
To be most efficient, the selected candidate will develop of these techniques focusing on the challenges emerging in a specific and particularly innovation driven domain of smart management and operation of low voltage distribution grids. In practice, these techniques will include novel beyond-state-of-the-art stochastic forecasting methods that can support the construction of live-scale, accurately finetuned and reliably robust digital twin (statistical simulation models) that capture the electrical aspects of the low voltage distribution grid. From the point-of-view of the distribution network operator, this approach tackles the most urgent challenges caused by the energy transition (electric vehicles, distributed electricity production, residential demand response, etc.), and has the added advantage of a high valorisation potential.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing competitive MSCA-IF proposals.

• Collaborations
The need and opportunity for collaboration with other research institutions and with relevant partners in industry will certainly emerge and are even a necessity. This can potentially result in secondments at the premises of one or more such partners. Collaboration with Belgian and European DSO’s will probably turn out to be of the highest importance for relevant data-access.

• Deadline application to VITO
Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, before Friday 17 April 2020 17h Brussels time.

 

Deadline MSCA-IF 2020: Wednesday 9 September 2020 17h Brussels time.

VITO contact details:
Dr. Koen Vanthournout
Unit ETE / Group AMO / VITO - EnergyVille
VITO: Boeretang 200, 2400 Mol, Belgium NV (Headquarters)
EnergyVille 1: Thor Park 8310, 3600 Genk, Belgium (place of work)
tel: +32 14 33 59 16

 

Qualification

We invite applicants to propose a more detailed and focused research approach within the scope of this MSCA-IF Fellowship as a part of their application. We are primarily looking for experienced researchers who wish to use this period as an opportunity to further develop their research, and to develop longer-term research collaborations with VITO and other institutions conducting research in the field.
The candidates as in principle must be eligible for a Marie Curie Individual Fellowship – please refer to the conditions set-out in the H2020 MSCA Work Programme.

The candidate will have a PhD in a data-science related field.
Important assets that increase her/his chances of selection include:
• Affinity with and/or strong interest in electrical energy systems and the potential of smart grids to increase the share of renewable energy.
• A drive to deliver research results that are novel to the scientific community and at the same time have potential for real-world applications in the field.
• Combine a self-motivating and independent attitude towards research as an independent thinker with the potential to thrive in collaborative setting as a team player.
• Take pride in the potential for applications of your research and in its relevance as well as in its scientific novelty and relevance.
• Eagerness to help tackle the challenges of Climate Change

The following assets will also be advantageous:
- An excellent track record in research, necessary for being able to develop a competitive Marie Curie Fellowship application;
- Publications of relevant research work in prestigious scientific journals;

- An open and cooperation-oriented nature, but with strong abilities for independent research work;
- Highly proficient in spoken and written English.

Offer

 

Initially, we offer assistance in developing competitive Marie Curie Individual Fellowship proposals.

Then, to successful applicants to the Marie Curie program, we offer;
- An exciting opportunity at VITO, the independent Flemish research organisation in the area of cleantech and sustainable development. Our goal? To accelerate the transition to a sustainable world;
- Participation in a dynamic professional research & innovation community;
- Flexible working conditions;
- An inclusive and friendly work environment;
- On-boarding assistance and other services.

 

 

Requisition

Location: 
Genk
Jobfield: 
Postdoc
ID: 
29300