305 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" positions in Denmark
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enhance machine learning performance; novel chip design strategies prioritizing efficiency and cost; verification of digital designs; advancements in electronic design automation (EDA), especially for AI
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Assistant Professor (tenure-track) and Associate Professor (tenured) Positions in Computer Scienc...
with core computer science or AI, and must be able to teach computer science courses at the bachelor and master levels. The ACP section Successful applicants will join the section of Artificial
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations of machine
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to new projects. Assist with troubleshooting their machines and support their understanding of core concepts. Guide students in working on their own project. Demonstrate best practices and foster
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming
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in Computer Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field Has strong theoretical and practical experience in deep learning Has hands
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in electrical engineering, computer engineering, computer science, or similar. Strong background in communication systems, optimization, or machine learning for networked systems. Experience and
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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we are seeking a highly talented and motivated PhD student within the field
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Job Description The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we are seeking a highly talented and motivated PhD student
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joint project with the pathology at OUH. Here, the student shall develop statistical and machine learning approaches to identify potential cancer on whole slide scans. The student contributes