Sort by
Refine Your Search
-
Listed
-
Field
-
(optional). Person specification: Prior experience in computer coding (e.g., Python, SLiM), AI modelling, and understanding of evolutionary or conservation genetics / genomics is desirable. Good teamwork
-
, are crucial for modelling volcanic processes and are vital for understanding the transitions. Geophysical monitoring provides essential information to constrain these parameters and inform decision
-
models. The project’s key objectives are to: 1) Identify critical indicators relating to ecosystem health and resilience; 2) Incorporate indicators into DBN models to simulate how ecosystems respond
-
intensifying upper ocean mixing processes. However, major gaps in our understanding remain due to challenges in observing and modelling the Arctic Ocean. Research Methodology The aim of this project is to
-
extending the existing VL dataset. Design and evaluate DL models capable of classifying marine litter types using multispectral data, with a focus on achieving robustness to varying spectral channel
-
model to resolve wheat planting strategies that can be used to safeguard biodiversity and suppress rust outbreaks. Training You will be embedded in the international and multidisciplinary Saunders Lab
-
other at policy-relevant scales, while ‘top-down’ estimates, based on atmospheric measurements and modelling, are hampered by large natural fluxes of CO2 between the terrestrial biosphere and the
-
observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
-
: adapting existing models of bird movement and migration to test hypotheses about the ecological processes shaping observed connectivity patterns. Identify species and populations that have the highest