National Technical University of Athens (NTUA) is looking for an Early-Stage Researcher (ESR) to work on the GECKO project under the HORIZON 2020 call.
Smart technology is everywhere - in our homes, pockets, and networks. Is smarter use of energy essential for low-carbon energy systems of the future?
Or is smartness just a buzzword for new gadgets that require ever-more energy and worsen the digital divide? Smart technology is a mass of hopes, fears and contradictions.
This PhD offers a unique opportunity to tackle energy-related issues and uncover consumption patterns, supported by a major new EU-wide PhD training network.
This interdisciplinary GECKO’ network connects leading social, computer and data scientists working on smart technology, artificial intelligence, human-computer interaction, energy, climate change, and responsible innovation.
GECKO will target interpretable and explainable Artificial Intelligence (AI) and explore alternative methods to build machine learning (ML) models drawing on the latest developments in information and social sciences.
An inter-disciplinary methodology will be adopted to tackle the most prominent application example driver, where ML and social science must be considered together : addressing urgent sustainability and energy efficiency needs, where a successful responsible AI technology must embed social science understanding of people’s actions and how they interact with technology.
GECKO will train the next generation of research leaders in this exciting and emerging field at the intersection between smart technologies, energy, big data, algorithm design, and user behavior.
The candidate will work on applying deep-learning techniques on energy signals to improve semantic description of energy signals and identify key consumption patterns.
The 36-month program will allow the ESR to work within a multidisciplinary team, enhance his / her knowledge on deep learning techniques and help addressing urgent environmental needs.
Exciting benefits are also part of the program, such as :
Skills / Qualifications
The ideal candidate should :
1) Have a strong background in programming and machine learning (can be showcased through curriculum courses or certified courses on online platforms).
2) Have work experience with Signal Processing (ex. images, video) in a research environment.
3) Possess programming experience in languages such as Python, Matlab and C++ as well as Python-related deep learning frameworks (ex.
Keras / Tensorflow, Pytorch). Knowledge of additional programming languages is a plus.
4) Have knowledge of the German or Swedish language (level C1 or higher), due to secondments in the aforementioned countries.