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contemporary retreat patterns influenced by anthropogenic climate change. The research will combine advanced remote sensing techniques with ultra-high-resolution analyses of lake sediments to reconstruct glacier
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structure of observable algebras in quantum field theory. This project looks at time observables as quantum reference frames of both quantum mechanical and quantum field theoretic systems, described by
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using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and
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to an ideal learing setting. The candidate will contribute to understanding how neural networks extract the most relevant information of the data to make a prediction using advanced mathematical tools
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field of research The PhD candidate will investigate how early autophagy structures form at the ER, with a focus on membrane remodeling and cargo-selective autophagy. The project addresses fundamental
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consisting of both control theory (or related fields) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization
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to develop methodologies for real-time modeling and inversion of geophysical well logs, with a particular focus on borehole electromagnetic data during drilling. This includes the further development
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strong skills in mathematical modeling and a clear motivation to work on applied geophysical problems. The ability to work independently and in a structured manner, along with strong collaboration skills
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domainspecific knowledge with data
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modeling is an advantage Knowledge of the northern North Sea rift system and the onshore geology of Norway is an advantage Applicants must be able to work independently and in a structured manner and