Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
machine learning methods to the analysis of large-scale astronomical datasets, with a particular emphasis on time-domain astronomy. Research directions will be flexible and shaped according to mutual
-
optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
-
publication or output forums for games, interactive media, animation, game visual development, computing or machine learning/AI is essential. This position will focus on advancing the technical foundations and
-
, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
-
. Job Requirements: PhD degree in Computer Science, Computer & Electronics Engineering or other related fields. Strong background and knowledge in at least one or preferably more of the following fields
-
for active learning. The role will work at the intersection machine learning, high-throughput computation, and inorganic crystalline materials discovery, focusing on accelerating the design and
-
an outstanding researcher whose prime interest involves the following research areas: Statistical Genetics / Omics Spatial Statistics Functional Data Analysis AI / Machine Learning in the healthcare space Or any
-
, 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
-
Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different