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biomedical research. Your profile Master's degree in computer science or related discipline Experience with Python and recent deep learning frameworks (e.g. Pytorch, MONAI) Strong interest in image analysis
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learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing and implementing NLP pipelines for clinical text processing, semantic annotation
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costs and energy requirements of state-of-the-art deep learning models significantly, while democratizing them for a vast community of users, researchers, and practitioners. The task is to perform just
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/ knowledge in the following areas: Solid background in motion planning and control of mobile robots Background in SLAM and SA models Background in Reinforcement and Deep Learning in robotics with a focus on
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processing Graph signal processing Machine learning - supervised, unsupervised and reinforcement and tools such as TensorFlow, PyTorch, Keras and GreyCat Neuromorphic computing, spiking neural networks Deep
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methods Excellent programming skills and familiarity with modern deep learning frameworks Strong interest in interdisciplinary research, and the ability to engage meaningfully with collaborators from
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Learning, particularly Graph Neural Networks, Transfer Learning, Deep Reinforcement Learning, and Transformer-based models, including hands-on implementation Strong understanding of machine learning models
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in at least one major programming language, such as Python, is expected Familiarity with deep learning frameworks and modern NLP toolkits is an advantage Motivation to publish research results in