Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
project working to develop real-time vector-borne disease risk assessment in low resource areas. The individual will be directly responsible for the development of adaptive predictive models for nowcasting
-
including forecasting models to predict the expected distribution of pests on the field to landscape scale. The research is expected to make pest forecasts and link them to the existing expertise in crop
-
field. This approach is related to data assimilation, allowing for better prediction, control, and optimisation of turbulent systems in engineering, energy, and environmental applications
-
) to Volumetric Arc Therapy (VMAT), Stereotactic Radiosurgery (SRS), and ultra-high dose-rate (UHDR-FLASH) therapy, the need for real-time control and verification becomes critical. This PhD will further develop
-
requirements in model serving Implement encryption and key management for model artifacts and sensitive data Set up secure access controls using cloud-native security services (e.g., KMS, Cloud KMS, Key Vault
-
quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
-
anticipating crises. Current landslide prediction models, based mainly on rainfall thresholds, become ineffective in the presence of snow cover. Snow acts as a temporary reservoir, storing precipitation before
-
types will change under different climate change scenarios based climate projections. This framework will be ultimately included in a flood prediction model, which will be developed within the VIDI
-
Predictive Model” project financed from the funds of Priority 2 of the European Funds for a Modern Economy Program 2021–2027 (FENG) Action 2.2 First Team, with the Intermediate Institution being the Foundation
-
effectiveness and toxicity of the treatments. Other duties: Develop and validate cancer risk prediction models using deep neural networks based on semistructured data. Develop and validate learning strategies