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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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applications in statistical genetics, developing new theory, algorithms, and scalable implementations. Starting date as soon as possible and upon individual agreement. The fellowship period is three years. A
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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 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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Biotechnology, Bioengineering, Biochemistry, Pharmaceutical Sciences, Neurosciences, Biomedicine, Biomedical Research or Genetics and be enrolled in a PhD or a non-degree course, relevant for the development
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Science Center has an opening for a graduate student researcher in Mathematical Optimization for large-scale power systems planning. They will deploy developed optimization algorithms on DOE high
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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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on high-fidelity modelling and test data for both metals and thermo-set composite materials. To achieve this we will explore the use of advanced genetic algorithms and/or Artificial Intelligence (AI