26 to 27 of 27 Random Forest Jobs in the UK

use. We’ll rely on your in-depth knowledge of the ML ecosystem and understanding of varying approaches - whether it’s neural networks, random forests, gradient-boosted trees or sophisticated ensemble methods - to aid decision-making so we apply the right tool for the problem at hand. Your work ...

plantation mapping by region – palm oil, cocoa, coffee, rubber, soy, timber and similar – in support of EUDR compliance and supply‐chain due diligence. Forest degradation and biomass/canopy‐height estimation from multi‐sensor fusion. Develop ARR feasibility models that fuse climate, soil, and remote‐sensing inputs to estimate … evaluating, and debugging ML models across the modern Python stack – deep learning (CNNs, U‐Nets, vision transformers) using PyTorch, and classical methods (gradient boosting, random forests) with scikit‐learn. Demonstrable experience with remote sensing data (optical, SAR) and an understanding of the sensor‐specific quirks that matter for modelling. ...