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methods including machine learning methods to integrate genomics, transcriptomics and epigenomics data set to uncover genomic-epigenomic interactions and cancer evolution trajectories. The tasks will
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will contribute to, and lead, include: Building and operating ultra-high vacuum and laser systems. Building electronics and automation schemes. Learning/operating fabrication and characterization
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points Participating in active research environments including a stay at another research team Obtain experience with teaching or other types of dissemination related to your PhD project Teach and
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work situations (strategic time managing); be flexible to adjust one’s own behavior and thinking according to the (relevant/local) context so as to attain the desired goals (learning ability) Language
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used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
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scholarship, to contribute to the project’s substantial collective prosopographical work (among other things with the aim of creating a new version of VisuaLeague ), and to learn and grow as a scholar together
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field