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Field
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radiation therapy treatments. At least one position will be offered to a researcher that has experience in deep learning and AI development and a willingness to apply these approaches in radiation therapy
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Engineering, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, AI, etc. Strong background in autonomous driving, deep learning, interaction modelling, prediction, robotics
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.) during medical imaging and radiation therapy treatments. At least one position will be offered to a researcher that has experience in deep learning and AI development and a willingness to apply these
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: Proficiency in Python and major deep learning frameworks such as PyTorch or TensorFlow Familiarity with transformer architectures and large language models (e.g., BERT, GPT) Experience in building, training
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with a PhD in computer science or bioinformatics are encouraged to apply. We create statistical, machine learning, and deep learning approaches for the processing of this data, with a major focus on
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research and learning. Incorporates advanced methodologies such as deep neural networks and language/multimodal models, leading the preparation of scientific Required Department Minimum Qualifications: Ph.D
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programming languages such as C and Python Proficiency in deep learning frameworks such as Pytorch and Tensorflow Knowledge in imaging and computing device and equipment Good written and oral
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-life environments. The Role: As Research Fellow on the COG-MHEAR project, you will have the opportunity to use your strong background in deep neural networks and multimodal hearing-aid signal processing
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and managing scalable ETL (Extract, Transform, Load) pipelines to integrate multi-source, multimodal datasets Applying big-data analytic, including spatio-temporal modeling and deep learning techniques
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning