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Field
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Innovation Leads Research Fellows (RFs) and Research Engineers/Assistants (RE/RAs) in the end-to-end development and productisation of solutions, including experimental design and prototype validation. Lead
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mammary epithelial cell systems · Mouse and genetically engineered cancer models · High-content and live-cell imaging · Tumor evolution and therapeutic response modeling Research
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childhood cancer The lab has extensive expertise in: · Human primary mammary epithelial cell systems · Mouse and genetically engineered cancer models · High-content and live-cell imaging
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: · Human primary mammary epithelial cell systems · Mouse and genetically engineered cancer models · High-content and live-cell imaging · Tumor evolution and therapeutic response modeling
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to their host and antibiotics and to translate these insights to develop innovative approaches to prevent, treat and diagnose bacterial infections. In particular, we are interested in understanding: i) how single
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following skills and experience: A recent PhD graduate in computer science, engineering and supply networks, artificial intelligence, machine learning, or a closely related field. Knowledge of and experience
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foundation models, fine-tuning & prompt engineering Physics-Informed Neural Networks & hybrid models Deep Reinforcement Learning for process optimization GANs, VAEs, diffusion models for synthetic data
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appointed for more than one PhD Research Fellowship period at the University of Oslo. Place of work is the Department of Technology Systems at Kjeller, Lillestrøm. Job description The Martian atmosphere is a
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diseases. Exploring molecular mechanisms linking to cancer, obesity, liver, women diseases using a combination of biochemical and molecular techniques in cultured cells, xenografts, and engineered mouse
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, our research is dedicated to unravel how bacterial pathogens functionally adapt to their host and antibiotics and to translate these insights to develop innovative approaches to prevent, treat and