PhD student
Joseph Jenkins
Joseph’s PhD aims to investigate the use of machine learning for estimating the expected trajectories of floating objects at sea. Precise estimations of trajectories is important for applications such as search as rescue, but the achievable precision is currently limited by the precision of modelled surface currents. His work aims to overcome this limitation by leveraging the recent advancements of deep neural networks applied to structured data, for example by exploiting relevant information in ancillary data such as sea surface height and temperature.
Joseph’s PhD is funded by a CIFRE grant, as a collaboration between the MIO and LIS institutes at the University of Toulon, France, and Datlas/Oxalis in Grenoble. He is co-directed in his work by Dr Yann Ourmières, MIO (Mediterranean Institute of Oceanography, UMR CNRS), Dr Adeline Paiement and Pr. Hervé Glotin, LIS (Laboratoire d’Informatique & des Systèmes, UMR CNRS), in collaboration with Clément Ubelmann, as his scientific and industrial advisor from Datlas, Grenoble.