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to machine learning, ocean modelling, neuroscience, drug discovery and medicine. The prospective PhD candidate will work in close cooperation with the researchers of the ATLAS group as well as Porta Mana
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. Proficiency in deploying and managing wildlife camera‑trap networks and processing large image datasets. Experience developing and validating machine‑learning and AI models for image object detection and
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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Computer Science or a related field Proven ability to conduct independent research with a relevant publication record. Outstanding data analytics, mathematical, and computer modelling skills. Excellent interpersonal
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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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. Experience in multimodal data fusion (e.g., MRI, EEG, and health records). Background in computational modeling and machine learning. Background Investigation Statement: Prior to hiring, the final candidate(s
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an emphasis on technology, data science and the humanities. LKCMedicine is searching for a Research Associate/Fellow in the field of Learning Analytics (LA) / Machine Learning (ML) under Professor Andy Khong
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: Strong understanding of statistics, probability, optimization, and linear algebra. - Machine Learning: Deep learning, probabilistic modeling, generative models, etc. - Programming & Software Development
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uses. To investigate feature-level just-noticeable difference modelling for machines to facilitate assessment and optimization. To formulate a comprehensive visual feature codec for machine uses
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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning and deep learning algorithms for dynamic systems (sequential or time-series data). Experience