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, the center will address a diverse and impactful set of use cases: Logistics, shipping and business transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and
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, CRISPR technology, chemical screening platforms, and precision oncology. Responsibilities Develop and optimize in vitro models and methodologies to investigate cytotoxic lymphocyte-mediated cancer cell
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, differential equations, geometry/topology, numerical analysis, optimization, and statistics. Part of the research is also carried out in close cooperation with other fields of science and technology at NTNU, as
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-water settings. The research will develop a unified framework that fuses heterogeneous sensing modalities through uncertainty-aware probabilistic optimization while maintaining semantic, structural, and
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and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship surveillance; Decarbonization and energy management; Autonomous ships and remote control. The research
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Supervised/unsupervised fine tuning of the existing models (e.g., Retrieval-Augmented Generation, Low-Rank Adaptation, Direct Preference Optimization, Reinforcement Learning from Human/AI Feedback). Moreover
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the sensory and functional qualities of natural seafood. This PhD project is expected to develop technology for cultivated seafood, by selecting the optimal cell source, developing a continuous cell line and
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for simulation or optimization of climate, energy, or transport systems (e.g., Fortran, Python, GAMS, XPress, Matlab). Competence in data processing and parsing, as well as data management. Strong analytical
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on pre-existing/collected data using Supervised/unsupervised fine tuning of the existing models (e.g., Retrieval-Augmented Generation, Low-Rank Adaptation, Direct Preference Optimization, Reinforcement
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in crystalline rocks. Drilling optimization using machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use