Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
dives into data from online consumer feedback and the embedded environmental footprints of each stem. This project will focus on the interface between the product’s aesthetic and data-augmented generative
-
. Data-driven methods (including machine learning) may be used to support and enhance these models. No prior experience in all areas is required — full training provided through the Fusion CDT. You will
-
representation of streamlines inferred from geomagnetic data, from Finlay et al. Nat. Rev. Earth Environ., 4:377–392, 2023 and numerical simulations by Schaeffer et al. Geophys. J. Int., 211(1):1–29, 2017
Enter an email to receive alerts for data-"https:"-"https:"-"https:"-"inserm" positions