Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
pathway prediction. Apply deep learning techniques to predict reaction outcomes, optimize reaction conditions, and identify novel synthetic routes. Curate and manage reaction datasets from literature
-
., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer
-
the roles of water and atmospheric physics and chemistry in forming soils (top and deep soils) and how the use of the topsoil for agriculture interacts with geochemical processes. The candidate is expected
-
deep learning techniques to improve image processing and trait prediction. Analyze large datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress
-
physics and chemistry in forming soils and how the use of the topsoil for agriculture interacts with deep soil (weathering profile) and vice versa . This person should have a good understanding of methods
-
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
-
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
-
About Mohammed VI Polytechnic University (UM6P) Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning, that is committed to an educational system
-
at a reduced cost. In this context, we are looking for a highly motivated postdoctoral researcher to join our team at the CRSA to develop AI models, specifically deep learning approaches, to analyze and
-
activities. Qualifications: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural