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Responsibilities The objective of this post is to offer interdisciplinary training to individuals interested in utilizing cognitive neuroscience and machine learning techniques to study learning, cognitive
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Sciences, Chemistry, Physics, Computer Science, or related disciplines with a strong background in computational methods and machine learning. Experience in materials informatics, high-throughput
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informed neural networks (PINN) and explainable machine learning (EML) frameworks; experience in related technologies including large-scale data analysis, deep learning, Python, PyTorch; and the ability
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experience in one or more of the following areas: development of methods for multi-omics data integration, application of machine learning models in life science, single cell data analysis and spatial
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basic principles of statistics, machine learning, and LLMs. Proficiency in at least one programming/scripting language (e.g., Python, R), along with strong experiences in relevant libraries and frameworks
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I/II (holding the functional title of Project Assistant) in the e-Learning Development Laboratory (url: https://elearning.eee.hku.hk/ ) of the Department of Electrical and Electronic Engineering (Ref
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Biological Sciences, preferably in ophthalmology or computer sciences or statistics or public sciences; (ii) proficiency in English; (iii) solid experience in ophthalmology and visual sciences research, deep
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) programmes. Applicants should have (i) a PhD degree from the University of good QS World University Rankings, special in Biological Sciences, preferably in ophthalmology or computer sciences or statistics
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basic principles of statistics, machine learning, and LLMs. Proficiency in at least one programming/scripting language (e.g., Python, R), along with strong experiences in relevant libraries and frameworks
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. Knowledge and skills in mathematics, biostatistics, or advanced statistical techniques in clinical research, database management, and machine learning (AI) will be taken into account. They should have