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Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural contexts in which digital narratives are received and processed. We investigate the ways
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at the University of Bergen. The Department hosts the Center for Digital Narrative (CDN) , a Norwegian Centre of Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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wearable devices using digital knitting and advanced fabrication techniques. Motion Sensing & Data Processing: Implement and optimize algorithms for joint motion tracking, integrating signal processing and
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analyses in nonclinical drug development. The postdoctoral role involves designing and implementing algorithms for anomaly detection, segmentation, and classification to contribute to the development
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Numerical Simulations of Complex Dynamic Systems, E.g. Turbulence, Hurricane. The duty of the role is within the range of: 1) developing novel algorithms on data analyses and data mining, e.g. Large Models
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. Material Optimization: Use optimization algorithms to design FGMs that meet demanding performance criteria like fatigue resistance and durability. Systems Integration: Apply a systems engineering approach to
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the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world
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to implement and optimize AI/ML models for biomedical datasets. Preferred Knowledge, Skills and Abilities Mathematical Modeling: Strong foundation in numerical modeling, graph theory, and statistics. Algorithm
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Theoretic algorithms of defense, and how those can/should be modified to account for human attacker’s biases. To accomplish this goal, we study attacker’s behavior and create cognitive computational models