Post/s of Part-Time or Full-Time Research Support Officer II or III or IV
QMLA – “Quantum Machine Learning for Astronomy” Xjenza R&I Thematic Programme - Digital Technologies Programme.
The full-time post is for a period until 30th October 2027. The candidate should preferably be available to start working with immediate effect. The post carries the following initial remuneration per annum / per hour, inclusive of any cost-of-living adjustments:
RSO II - €30,327/ €14.58;
RSO III - €36,692 / €17.64;
RSO IV - €47,092 / €22.64.
This project investigates the application of Quantum Machine Learning (QML) algorithms, with emphasis on astronomical data analysis. Current analysis methods often struggle to extract faint astronomical signals obscured by noise within large, high-dimensional datasets, hindering progress in our understanding of the cosmos. By developing resource-efficient QML models tailored for astronomical data, we aim to achieve significant advancements in three key areas. Firstly, we aim to enhance signal detection capabilities, potentially leading to the identification of previously undetectable objects or faint signals from distant galaxies. Secondly, these QML models will be trained to improve feature recognition within the data, providing deeper insights into the characteristics and behaviours of astronomical objects.
More information available at
https://www.um.edu.mt/media/um/docs/directorates/hrmd/workatum/projects/...
