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Dr Edward Johns, as well as a larger team across the UK as part of the ARIA-funded Robot Dexterity programme (see: https://www.aria.org.uk/opportunity-spaces/smarter-robot-bodies/robot-dexterity
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optimization, with experience in adaptive routing and SDN technologies. Proficiency in programming languages such as Python, C/C++, and experience with parallel computing frameworks. Effective written and oral
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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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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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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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than 30 people, including parallel post-doctoral researchers in four other countries, and led by Prof Ben Baumberg Geiger at King’s. Secondly, it’s located within the Centre for Society and Mental Health
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Global Critical Zone Science Chair to develop and conduct a research program to better understand forest nutrition and nutritional stress in Eucalyptus forest stands in Brazil. Research context: Forests
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screening (e.g., luciferase assays, high-content imaging, massively parallel/multiplexed assays, etc.) is desirable. Ability to interpret and discuss experiments and critically contribute to writing
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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lattice field theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging