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the design of antibody modalities Documented experience from cancer-related research Documented research experience in AI/machine learning/deep learning Documented experience in the development of therapies
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functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Deep learning for imaging of marine
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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research tasks, mentoring junior researchers, and coordinating multi-stage projects. Fluency in Python and modern deep learning frameworks (PyTorch/TensorFlow). Strong analytical, communication, and academic
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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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000 individuals in UK. As part of a wider strategy to develop a deep human experimental medicines platform, this project aims to mainly focus on using novel human in vitro platforms using IBD gut stem
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, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7
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UiO/Anders Lien 9th February 2026 Languages English English English Join a vibrant team at the University of Oslo as a PhD Research Fellow in Deep Learning for geoscience imaging! PhD Research
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Classification Title: Assistant/Associate/Full Professor Classification Minimum Requirements: a Ph.D. in computer science or related field Expertise in AI/ML, deep learning Expert proficiency in
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
of the trajectory. This grant targets the development and rigorous benchmarking of novel, energy-efficient CAD-based deep learning architectures that fuse visual and inertial modalities for the robust 6D pose