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interface of machine learning, statistics, probability, and with applications in statistical genetics, developing new theory, algorithms, and scalable implementations. Starting date as soon as possible and
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at the interface of machine learning, statistics, probability, and with applications in statistical genetics, developing new theory, algorithms, and scalable implementations. Starting date as soon as
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it may use population-scale genetic, clinical, or public health data from pathogen surveillance efforts and biobanks. We are looking for a PhD student in Molecular Biology and a special interest in any
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& Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame
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. The project is based on a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University and SciLifeLab . About the DDLS research program The PhD
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The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic architecture of important crop traits, such as grain yield, adaptation
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experimental data are now available or it may use population-scale genetic, clinical, or public health data from pathogen surveillance efforts and biobanks. The future of life science is data driven. Will you be
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biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may use population-scale genetic, clinical, or public health data from pathogen
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral
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experimental molecular biology and data analysis. Doctoral candidates can specialize in genomic and molecular biology techniques, as well as in algorithms, statistics, and artificial intelligence for molecular