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cancer or relapse to identify genetic alterations that may be targetable with novel drugs. A main component of this project will be to characterize the genomic and transcriptomic landscape of our patient
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methods to directly probe the phase behavior, i.e., the number and types of phases, in individual aerosol particles, and to explore how it affects their ability to form clouds. The project will focus
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also have responsibilities related to training other team members in relevant skills, fostering a collaborative and educational atmosphere within the group. The project involves a mixture of method
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of field-grown vegetables or agricultural crops, and master state-of-the-art experimental and analytical methods in plant physiology, agronomy and agroecological research. You are expected to have research
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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for an extension of at least 1 additional year, based on performance and upon mutual agreement. Description of research project This project aims to develop novel methods to directly probe the phase behavior, i.e
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approaches or novel microphysiological methods. - Possess or be willing to develop coding skills (R or Python) for large-scale metabolomics and/or proteomics data analysis. - Demonstrate a track record of
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mechanistic understanding of the structure-properties relations for complex heterogeneous materials by exploiting synergistic combinations of computational, experimental and machine learning methods. A key
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of field-grown vegetables or agricultural crops, and master state-of-the-art experimental and analytical methods in plant physiology and agro-ecological research. You are expected to have research experience