Αποστολή βιογραφικών έως
31 Μαΐου 2021
Επιστημονικό ΑντικείμενοΗλεκτρολόγων Μηχανικών και Μηχανικών Η/Υ Πληροφορική
ORGANISATION/COMPANY Intracom Telecom
RESEARCH FIELD Computer science › Modelling tools Engineering › Electrical engineering Engineering › Knowledge engineering
RESEARCHER PROFILE First Stage Researcher (R1)
- APPLICATION DEADLINE 31/05/2021 17:00 – Europe/Athens
- LOCATION Greece › Peania
Intracom SA Telecom Solutions is seeking to hire an Early-Stage Researcher (ESR) for a 36 Person Months contract in the context of the Marie Skłodowska Curie Action – Innovative Training Network (MSCA-ITN) project “GECKO” (Grant agreement ID: 955422), with parallel enrollment into a Ph.D. program at the National Technical University of Athens (NTUA), Greece.
The GECKO project (https://gecko-project.eu/) scope is built around interpretable and explainable Artificial Intelligence (AI) and explores alternative methods to build machine learning (ML) models, drawing on the latest developments in information and social sciences. An inter-disciplinary approach will be adopted to tackle exemplary applications where ML and social science must be considered together, such as sustainable energy and energy efficiency.
The objective of this PhD fellowship is to investigate different, machine learning-guided methodologies for a flexible energy approach towards distributed energy-related assets integration in flexibility markets. The ultimate objective will be to integrate the best approaches into an IT solution that i) aggregates and analyzes data from smart home-related Internet of Things (IoT) platforms and smart devices, therefore establishing a comprehensive basis for precise energy disaggregation, ii) considers the outcome of this analysis along with the household habits and comfort levels towards forecasting the energy demand and flexibility, iii) calculates the available capacity of local storage and the forecasted generation of small-scale (residential) renewable sources, and iv) combines the above outcomes towards determining optimal consumption patterns when sourcing a household’s energy flexibility in flexibility aggregation and management schemes and novel energy markets.
The expected results include:
- A set of novel ML-based forecasting methodologies for households’ energy consumption, generation and flexibility. The novelty of the methods has to be documented by at least two publications in international journals with impact factor with the PhD candidate as a main author.
- A software platform that manages the pre-processing, analysis and presentation of data from existing IoT platforms, smart devices and smart meters, and applies the methodologies of (1) towards the formulation of an optimal strategy for sourcing a household’s energy flexibility in flexibility aggregation and management schemes and novel energy markets.
Being part of the GECKO ITN the ESR will have the opportunity to work within a multidisciplinary team, enhance his/her knowledge on machine learning techniques and help addressing urgent energy related needs. Exciting benefits are also part of the program, such as:
- doing secondments in other organizations participating in “GECKO”
- multiple training and career development opportunities, such as training events, networking events and conferences
- being part of a vast PhD network of 15 researchers across 9 European academic and industrial institutions
- very competitive salary