Sort by
Refine Your Search
-
research in the field of machine learning, more specifically, deep learning and representation learning architectures. Application areas of ML include, but are not limited to, computer vision, natural
-
be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
-
holding a PhD in chemical, environmental or process engineering, to apply for a full-time post-doctoral fellowship position in the field of water desalination, focusing on the development of an artificial
-
. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and
-
· PhD in Materials science, chemistry, physics, polymer science, or related field · Strong background in ferroelectrets, piezoelectric materials, voided charged polymers or piezocomposites
-
using a combination of multimodal imaging, computer vision, and lab automation platforms that govern entire workflows (e.g. ThermoFisher momentum software scheduling Hamilton liquid handlers and high-end
-
to the development of mineral resources in Saudi Arabia by developing innovative approaches to mineral exploration, mining, and mineral processing. The working group will initially consist of 1 PhD student and 2 MSc
-
Applicants must have a PhD in Computer Engineering, Computer Science, or Electrical and Computer Engineering, and have published their research in prestigious conferences and journals in related
-
of their Ph.D. degree (up to one year into the future) are also encouraged to apply. PhD awarding university must be ranked in the QS Top 500 (2025 edition ) Essential Knowledge & Skills In-depth knowledge and a
-
project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict