The Department of Electronic and Electrical Engineering (EEE) within the Faculty of Engineering is looking for three highly-motivated PhD students to engage in cutting edge interdisciplinary AI research combined with a structured curriculum of training activities. The successful candidates will be fully integrated within the European Commission MSCA GECKO (https://gecko-project.eu) International Training Network (ITN) to work with 12 other PhD students within an interdisciplinary consortium of nine European academic and industrial institutions, with support from 6 European industrial partners and Stanford University.
You will be trained in an international, inter-disciplinary academic and industrial environment through state-of-the-art research, GECKO training schools, and secondments to academic and industrial institutions.
GECKO will target interpretable and explainable Artificial Intelligence (AI) and explore alternative methods to build machine learning models drawing on the latest developments in information and social sciences. The focus of GECKO will be on AI design that is robust, from both technical and social perspectives, since even with good intentions, AI systems can cause unintentional harm. With this in mind, GECKO will focus on sustainability in relation to end users, where the decisions made by AI can significantly and directly affect people.
The PhD projects will exploit model visualisation tools and response to dynamics of collected data to understand the reasoning behind machine learning outcomes; information extraction methods to meet privacy and trust requirements; and novel graphical inference and signal and information processing techniques to acquire understanding how deep learning methods transform input data into outcome recommendations. The successful candidates will interact closely with social science teams to integrate human/social elements in the machine learning models, including biases, inclusion, accountability, and provide computational methods to understand social phenomena, studying causal inference in social systems.
Specific eligibility related to these posts are:
For all recruitment, the eligibility and mobility of the researcher will be determined at the time of their (first) recruitment [appointment] in the project. The status of the researcher will not evolve over the life-time of a contract.
Subject Areas Include: AI & Machine Learning; Computer Science & IT; Electrical & Electronic Engineering; Energy; Software Engineering; Information Sciences; Applied Mathematics; Environmental Engineering; Applied Physics
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