You will be working as part of DRIVEN Doctoral Training Unit (DTU) funded by the FNR PRIDE scheme. The Computational and Data DRIVEN Science DTU will train a cohort of 19 Doctoral Candidates who will develop data-
driven modelling approaches common to a number of applications strategic to the Luxembourgish Research Area and Luxembourg’s Smart Specialisation Strategies.
DRIVEN will build a bridge between state-of-the-art data driven modelling approaches and particular application domains, including Computational Physics and Engineering Sciences, Computational Biology and Life Sciences, and Computational Behavioural and Social Sciences.
Research direction :
In the research direction Gravity Field estimation within the field of Computational Mechanics, the Doctoral Candidate will develop an algorithm to compute the direct gravitational attraction due to the water in an artificial reservoir in Luxembourg.
Gravity measurements are carried out in a gallery below the reservoir. The objective is to estimate universal gravitational constant G .
From the measured gravity changes, the size and dimension of the reservoir and from the water level variations, G is obtained by a simple inversion.
However, the water mass gravitational effect must be computed with high accuracy. Visualization and animation tools will play a big role in the study.
Moreover, the essential and primordial aspect will be to provide a complete accuracy assessment. Key parameters controlling the precision and accuracy of the results will have to be thoroughly investigated through extensive simulations and sensitivity studies.
Job description :
Your primary tasks as a DRIVEN fellow are to :
Your lead supervisor will be Prof. Dr. Olivier Francis. Further supervision will be provided by Dr. Jack Hale.