Sort by
Refine Your Search
-
languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and fine tuning techniques
-
transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models
-
technologies. The project focuses on exploring microbial communities and their molecular mechanisms for detoxifying and transforming heavy metals under environmental or engineered conditions. The successful
-
postdoctoral researcher will focus on the development of innovative high-temperature processes for the transformation, upgrading, or enrichment of mineral resources, particularly those derived from complex
-
computational power and the increasing availability of large volumes of remote sensing data with finer spatial and temporal resolutions have significantly transformed the way we approach climate and weather
-
validation of process engineering. CBS projects aim at an in-depth understanding of the molecular mechanisms of all transformations in order to propose new original alternatives in terms of efficiency
-
health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools to assess the impact of urban interventions on health. Smart City Experience: Experience in developing smart
-
for detoxifying and transforming heavy metals under environmental or engineered conditions. The successful candidate will contribute to ongoing projects and develop independent lines of investigation within
-
ability to work collaboratively in a multidisciplinary research environment. Preferred Skills: Experience in graph-based learning, attention mechanisms, and transformer architectures applied to chemical
-
neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view learning, transfer learning, and data fusion techniques to integrate heterogeneous omics datasets