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University Hospital. About the project/work tasks: The primary objective of this project is to develop novel radiometal complexes conjugated to bioactive molecules for advanced applications in PET imaging. PET
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environment within the research-based innovation Centre for Effective Engineering and Learning in Complex Systems, SFI CELECT . Its vision is to do more with less- and faster. Norway’s leading industrial
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VAMS, as sampling devices for complex biological samples like blood and serum. We have specialized in the determination of peptides and proteins in dried form from these devices. Furthermore, we have
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of Informatics at Blindern, Oslo. Job description Unsupervised machine learning (ML) methods are widely used to explore structure in complex and high-dimensional data, particularly in the life sciences, where
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machine learning (ML) methods are widely used to explore structure in complex and high-dimensional data, particularly in the life sciences, where clustering analyses often form the basis for biological
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knowledge of the complex interplay between genes and environments in shaping our health and the position we occupy on the social and economic ladder. More specifically, we use the quickly increasing
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suitable compressible gases no longer exist and the required infrastructure becomes prohibitively complex and energy intensive. Solid-state caloric cooling represents a promising and environmentally friendly
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and structural effects of various peptides on both simplified and complex membrane systems. The project will entail a combination of computational and experimental work, both directly and in
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), (c) estimation methods for latent variable models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d) meta-analytic models to address complex data structures (e.g., spatial
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of the Center for integrative neuroplasticity (CINPLA) and in the INTED center. This PhD project will focus on reinforcement learning methods for generating complex structures with two possible application areas