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Field
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to apply advanced AI models in areas such as catalyst design, multi-scale modeling, and spectroscopic analysis. The Research Fellow will take on a significant role in machine learning theoretical energy
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. Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular biology and/or gene regulation. Experience with nanopore sequencing, Hi-C, ribosome profiling, or CAGE data
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medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and astrostatistics. These posts
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Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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machine control for smart manufacturing as well as publications in top-tier international conferences and journals, as well as real-world implementations. If interested, please apply with your resume
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Engineering, Industrial Engineering, Machine Learning, Artificial Intelligence, or related fields Expertise in numerical simulation of multi-physics systems, especially fluidic problems Expertise in generative
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Are you keen to pioneer machine learning models that address the challenges of robot perception? We are recruiting a research fellow who will work on our EPSRC-funded research project on “Active
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology
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for Quantum Technologies (CQT) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices
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Intelligence (AI) and machine learning, digital sociology, AI and the sociology of knowledge, AI and expertise, and digitalization and criminology (digital criminology). A prerequisite for employment is that