Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
Job Description Job Alerts Link Apply now Job Title: Visiting Research Fellow for Quantum Algorithms Posting Start Date: 19/06/2025 Job Description: About the Centre for Quantum Technologies (CQT
-
/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
-
-driven control techniques for robot path/trajectory planning Implementation of the developed algorithms Algorithms and systems verification and validation Report writing and presentations Job Requirements
-
Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for communication networks. Key Responsibilities: Develop signal processing and machine learning
-
. The successful candidate will play a pivotal role in a project centered around variational quantum algorithm in the near-term, especially on innovating advanced error mitigation or detection techniques to solve
-
state-of-the-art facilities to work on the following: Developing advanced path planning, search, and exploration algorithms for multi-UAVs systems in unknown and complex 3D environments. Designing
-
team to conduct the research on development of AI models and algorithms for image processing, computational imaging as well as computer vision applications. The roles of this position include: Research
-
team to conduct the research on development of AI models and algorithms for image processing, computational imaging as well as computer vision applications. The roles of this position include: Research
-
, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
-
, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems