603 algorithm-"Multiple"-"U" "NTNU Norwegian University of Science and Technology" Fellowship positions
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present
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teaching hospital at the Flinders Medical Centre in South Australia to multiple rural clinical locations all the way to Darwin in the Northern Territory. Our research and teaching equip the next generation
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learning, and data science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood
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lab has ample opportunities to develop valuable scientific skillsets and make novel discoveries in cardiovascular science. Research in the lab receives funding from multiple external grants including
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) strong communication and organisational skills, with the ability to manage multiple tasks and meet deadlines. Preference will be given to those with strong proficiency in Cantonese. Applicants are invited