Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
embedded software for CubeSats. They will teach embedded systems and spacecraft engineering and lead experimental research on robust satellite architectures and mission reliability. Key qualifications: PhD
-
(DFT), and machine learning techniques to enhance simulation accuracy Simulation-driven materials design for energy storage, catalysis, membranes, and advanced functional materials Modeling of interfaces
-
and implement innovative image analysis methods to quantify plant characteristics. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and
-
. The main objective of the project is to study the interaction between machine learning and wireless communication fields. The successful candidate will answer questions such as how to assign limited
-
candidate in the area of machine learning for IoT networks. The candidate must hold (or about to complete) a PhD in the related fields shown below. The candidate is expected to have hands-on experience in
-
skills in machine learning, deep learning, and advanced statistics for processing complex data. Urban Health Principles: Familiarity with urban planning principles centered on health (active mobility
-
embedded software for CubeSats. They will teach embedded systems and spacecraft engineering and lead experimental research on robust satellite architectures and mission reliability. Key qualifications: PhD
-
internationally oriented institution of higher learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development
-
devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial
-
research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning