Sort by
Refine Your Search
-
, transportation systems and biological interactions. These systems are represented as networks. A network is a set of objects that are connected to each other in some fashion. Mathematically, a network is
-
real-world applications in green chemistry and industrial synthesis. Key Responsibilities: Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic
-
in some fashion. Mathematically, a network is represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the
-
Science and Society, but also by examining the truth of scientific theories (this is the role of the epistemologist) and the impact of putting them into practice (this is the role of the researcher in
-
learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
-
Mathematics, Data Science, or related fields. Strong background in Operations Research. Experience with industrial data processing, particularly in dynamic, real-time environments. Proficiency in machine
-
Département / Department : Unité / Unit:Center for African Studies Université / University:Mohammed VI Polytechnic University Intitulé de l’offre Postdoc / Title of the Postdoc offer : L’Afrique dans l’œuvre de Mokhtar Soussi Summary of the subject: One of the missions of the Center for African...
-
CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
metabolomics data from clinical studies. Apply deep learning models (e.g., autoencoders, variational autoencoders, graph neural networks) for biomarker discovery, disease classification, and patient
-
part of the project team. Applicant requirements Ph.D. in bioinformatics, proteomics, drug design and development, genomics, mathematics, computer science, or related fields Complete CV Short research
-
of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities