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genomic summary statistics (e.g., diversity, inbreeding, mutational load) Interest in machine learning applications (experience is a plus but not required) A strong understanding of evolutionary and
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and applying new skills. Experience with programming in Python and a working knowledge of statistics It would further be beneficial if you have some of the following skills: Hands-on experience with
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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including supervision of BSc and MSc students associated with the project As a formal qualification, you must hold a PhD degree (or equivalent). In the assessment of the candidates, consideration will be
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers