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Field
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required Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow) Experience with unstructured
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: PhD in CS/ML/medical informatics, strong publication record, and hands-on experience with generative models in medical imaging. Postdoctoral Research Associate (f/m/d) EU Research Project TWIN-X Full
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focused on deep-phenotyping of individuals with autism and controls including brain imaging (MRI, fMRI, DTI and EEG) and a battery of cognitive tests. Our group is currently developing new methods
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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imaging of breast cancer as per 1st of May 2026 or as soon as possible thereafter. The position is a fixed-term full-time position for 1 year. As a Postdoctoral researcher at the Department of Clinical
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reconstruction and processing. Candidates are expected to have a strong background in medical imaging, experience in imaging system evaluation, deep learning and clinical investigation. Brief Description of Duties
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strong background in shape modelling, deep generative modelling (diffusion/transformers), or multimodal representation learning. You have strong programming skills, especially in Python, and preferably
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reconstruction and processing. Candidates are expected to have a strong background in medical imaging, experience in imaging system evaluation, deep learning and clinical investigation. Brief Description of Duties
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structures and corresponding images) needed for training and validating deep learning (DL) models. Work closely with members of the ICMN nanostructures group or external collaborators. Communicate research
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Project Overview The DiSTAP programme addresses deep problems in food production in Singapore and the world by developing a suite of impactful and novel analytical, genetic and biosynthetic