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Field
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written communication skills. A collaborative mentality towards research and mentoring. Desired skills and techniques include experience in parallel computation and advanced numerical programming, using
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. Strong background in numerical linear algebra, algorithm design, and parallel computing. Proficiency in programming languages such as python. Experience with HPC environments and linear algebra
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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to increase catalyst activity and selectivity. The computational part of the project will investigate relevant reaction paths and evaluate spectroscopic signatures that can be compared to a parallel
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exposed to the biotech start-up community in the greater Copenhagen area. In parallel as part of PLEN, the Post Doc fellow will be interacting leading scientist within the fields of plant science and
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performance computing numerical methods in our state-of-the-art open source micromagnetic model, MagTense. MagTense is based on a core implemented in the Fortran programming language, and it relies
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2025, or as soon as possible thereafter. The project explores two parallel technological routes for converting captured carbon dioxide into microbial biomass: One fully biological, and the other a hybrid
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generative design tools such as HEEDS, and/or the Dakota or RAVEN uncertainty quantification tools. Experience with FORTRAN, C, and/or C++ applied programming. Knowledge of Python, Java, or other scripting
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with Python and R programming languages. Experience with functional genomic technologies including massively parallel reporter assays. Biomedical informatics or biomedical research experience. Preferred
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key