Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
-the-loop control for extreme robotics applications, including high performance algorithms for 3D perception, model predictive control, reinforcement learning, generative AI, and simulation and virtual
-
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
-
characterisation and heat-transfer measurements, and development of model-predictive control algorithms for dynamic charge–discharge operation. The postholder will support prototype fabrication, instrumentation
-
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
-
multimeric complex prediction. You have experience of microbiome sequencing, genome mining, or metagenomic data analysis. You have worked with host-pathogen interaction models, antimicrobial peptides
-
scientist. Job requirements Professional experience Machine learning / Deep learning tools (pytorch) and predictive modeling Bioinformatics analysis of omics data Education and training PhD or equivalent
-
fields). Strong quantitative skills and demonstrated expertise in predictive modeling and advanced computational methods (e.g., Multilevel Vector Autoregressive Models, Dynamic Structural Equation
-
recover quickly from disruptions. The research will involve reinforcement learning, predictive modeling, and real-time adaptive control to dynamically optimize production sequencing, resource allocation