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language models, multimodal generative AI, and related areas. Develop algorithms, architectures, and training methods for world models, LLMs, and multimodal AI systems. Design methods for prediction
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cancers (Dentro et al., Cell 2021), the evolutionary history of cancer (Gerstung et al., Nature 2020), biallelic mutations in cancer genomes (Demeulemeester et al., Nature Genetics 2022), combined DNA
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Details Title Postdoctoral Fellow in Cell Biology and Tissue Culture School Faculty of Arts and Sciences Department/Area Organismic and Evolutionary Biology Position Description Are you ready to
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developing/adapting computational models or algorithms to analyse biological data, and experience with single cell or spatial omics datasets or knowledge of cancer biology would be an advantage. What we offer
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system model new module integration, scenario simulations, and prognostics analyses Physics-informed deep learning/hybrid modeling/reasoning AI algorithm development and optimization Job Requirements: A
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framework to find the optimal operation strategy Conduct computer programming to verify the efficiency of the designed solution algorithms Analyze data acquired from the field survey Develop machine learning
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algorithms for: Fine-grained video understanding Concept learning Temporal reasoning Vision-Language Models (VLMs) Multimodal representation learning Self-supervised and weakly supervised learning Fine-tune
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settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors. Help guide and mentor graduate students and other junior team members working on the project
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environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software
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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Key Responsibilities: Designing and developing scalable algorithms