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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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other duties related to the research program. Job Requirements: A PhD in Computer Science or a relevant field. Strong background in deep learning, Generative AI, and multimodal learning. Strong
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at least one mainstream deep learning framework (e.g., PyTorch, JAX) • Expertise in (atomistic) thermodynamic, kinetic simulations or computational chemistry • Ability to independently design and
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depends on the background of a suitable candidate. The main topics of the group in the past few years were generative modeling, 3D reconstruction, image-editing, and deep learning using 3D data. More
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questions, advancing deep learning models, or other topics discussed with the PI. We use publicly available and simulated genomic data. Core job duties include: (1) Building computational pipelines
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Intelligence, Machine Learning, or relevant fields. Strong theoretical research capability, particularly in the theoretical analysis of optimization, convergence, stability, and/or generalization of deep
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related to heart failure and cardiovascular biology. Develop and apply machine-learning and deep-learning approaches to identify disease-associated cardiomyocyte subtypes, cellular trajectories, and
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an exciting place to learn and
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Computer Science, Artificial Intelligence, Mathematics, Engineering, or a related field. Entry level candidates with demonstrated expertise in artificial intelligence (AI), machine learning, deep learning
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processes under different biological conditions. Apply statistical learning, deep learning and probabilistic modelling approaches to large-scale cancer datasets. Evaluate and benchmark computational methods