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within this project include: Extending DeepRVAT towards non-coding genetic variation Applying DeepRVAT to population-scale single-cell readouts Integrating population data with experimental perturbation
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new coding languages will be preferred. Proficiency with advanced statistical analysis techniques, demonstrated through mastery of one or more of complex modelling techniques (e.g., multilevel models
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-coding RNA (lncRNA) genes in plant genomes. The Knut and Alice Wallenberg Foundation (KAW) funds this two-year postdoctoral scholarship. The scholarship amounts to 348 000 SEK per year and is not subject
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mathematical and computational techniques, it is essential to have experience in mathematical modelling / dynamical systems theory / numerical methods / coding. An ideal candidate would have a PhD, or
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transposon annotation, phylogenomics. Candidates must demonstrate proficiency in coding and analyses through open-access repositories (github or zenodo). This project will expand the lab existing genome
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extremes Reference code: 50141621_2 ? 2025/KS 2 Commencement date: as soon as possible Work location: Geesthacht Application deadline: June 18th, 2025 The department of Climate Extremes and Impacts
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimising PIC algorithms for modern
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. The HEXAPIC project aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimizing PIC algorithms
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of understanding their regulation by phosphorylation. You will be in charge of writing and testing code, developing, deploying and maintaining software. Your work will benefit from the experimental data generated by