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Field
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. Working closely with the ABI program’s leadership team, you’ll contribute to data curation, protocol development, predictive modelling, and novel analytics for large-scale neurocritical care datasets. As
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fundamental research into real‑world impact. You will design, model and fabricate advanced thermal management solutions that suppress conductive and convective losses in radiative cooling devices, then scale
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over India with Machine Learning’ (HEPPI-ML), which is funded through the ‘Weather and Climate Science for Service Partnership ’ (WCSSP) programme. It is also linked to the National Institute for Health
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will involve investigating the physiological and functional variation of plants using spectroscopy and will include greenhouse work, field work, plant phenotyping, computational analyses of hyperspectral
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Quantitative Genetics, Statistical Genomics, Computational Biology, Plant Breeding, or a related field. Strong expertise in GWAS and post-GWAS analysis (e.g., fine mapping, gene network modelling, GWAS boosting
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Computer Science, Mathematics, Physics, Applied Economics, or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning frameworks. Proficiency in
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such as quasi-normal modes. You will lead the development of modelling codes and have primary responsibility for at least one project within the broader research program. Additionally you will contribute
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information about AbbVie, please visit us atwww.abbvie.com . Follow @abbvie onX ,Facebook ,Instagram ,YouTube ,LinkedIn andTik Tok . Job Description Program Overview AbbVie needs outstanding individuals willing
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used to assess transfer of pathogen loads to fruits and vegetables. The microbial community changes and its influence on pathogen levels will also be quantified. These data will fit into models
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programming and computational modelling as core elements. Questions about the position For further information please contact: Anthony Mathelier Assistant Centre Director anthony.mathelier@ncmbm.uio.no