-
record of publications in reputable peer-reviewed journals in maritime transport, logistics management, machine learning, deep learning, or optimization Proficient in both written and spoken
-
. To collaborate with industrial and academic partners. To perform any other duties related to the research program. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics
-
geophysical investigation, geomechanical engineering, and machine learning. The Centre for Urban Solutions is to provide leadership in developing innovative solutions and sustainable technologies for space
-
, Artificial Intelligence (AI) & Machine-Learning (ML) applications. Good written and oral communication skills Proficiency in power system modelling, advanced control theory (e.g., model-predictive control, etc
-
theories in inverse/scattering problems. Once successful, the candidate is expected to transfer their expertise to machine learning/scientific computing in collaborations with other group members (phd
-
sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for Tunnel Boring Machine (TBM) tunnelling and excavation Developing large language model enhanced
-
Computer Science, Artificial Intelligence, Mathematics, Engineering, or a related field. Entry level candidates with demonstrated expertise in artificial intelligence (AI), machine learning, deep learning
-
road safety analytics framework. The role involves integrating multi-source transport datasets, developing advanced analytical and machine learning models for risk identification, and supporting
-
research in formal verification, machine learning and artificial intelligence system assurance. The successful candidate will develop new techniques and tools for analysing, verifying and improving
-
++, Java, Julia, or other competent languages. A good record of publications in reputable peer-reviewed journals in maritime transport, logistics management, machine learning, deep learning, and optimization