Efficient exploitation and recycling of the multi-sensor optical imagery leads to complete elimination or substantial reduction of the need for manual interventions during mapping and monitoring campaigns. The central aim of this PhD project is to develop and validate state-of-the-art statistical and machine learning techniques for synergistic use of multi-sensor data for the purpose of comprehensive object-aware scene analysis which includes both semantic interpretation and high-fidelity position estimation (geolocalization) of objects. This will be achieved by relying on data such as street level imagery, airborne/satellite optical imagery, laser scans and 3d point clouds obtained via Light Detection and Ranging (LiDAR) systems, as well as data originating from GIS static maps. The project will be supervised by Prof. V. Krylov in Dublin City University as part of the ADAPT research centre.
You are a motivated and enthusiastic person with a primary degree (e.g. Master’s degree) in computer science, statistics, machine learning, electrical engineering or related fields, with a strong interest in developing and implementing/prototyping machine learning and statistical techniques. Some prior experience with computer vision and/or image processing will be particularly relevant for this position. You are curious, have strong analytical thinking skills, and you communicate clearly in written and verbal settings.
As an ADAPT funded PhD researcher you will have access to a network of 85 global experts and over 250 staff as well as a wide multi-disciplinary ecosystem across 8 leading Irish universities. We can influence and inform your work, share our networks and collaborate with you to increase your impact, and accelerate your career opportunities. Specifically, we offer:
Each application should only consist of
For informal inquiries please contact Vladimir Krylov (firstname.lastname@example.org).
ADAPT is committed to achieving better diversity and gender representation at all levels of the organisation, across leadership, academic, operations, research staff and studentship levels. ADAPT is committed to the continued development of employment policies, procedures and practices that promote gender equality. On that basis we encourage and welcome talented people from all backgrounds to join ADAPT.