4 of 4 Permanent Random Forest Jobs in the East of England

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 … debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision transformers) using PyTorch, as well as 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. ...

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 … debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision transformers) using PyTorch, as well as 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. ...

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 … debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision transformers) using PyTorch, as well as 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. ...

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 … debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision transformers) using PyTorch, as well as 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. ...