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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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supervision experience at the BSc and MSc level Interest and experience in developing competitive national and international research applications Experience in programming languages (e.g. Python/R) and
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supervision experience at the BSc and MSc level Interest and experience in developing competitive national and international research applications Experience in programming languages (e.g. Python/R) and
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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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or laboratory analyses. Familiarity with statistical analyses and data integration across multiple sources. Collaborative skills and ability to demonstrate commitment in teams Motivation to pursue a scientific
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or laboratory analyses. Familiarity with statistical analyses and data integration across multiple sources. Collaborative skills and ability to demonstrate commitment in teams Motivation to pursue a scientific
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of metabarcoding data, plant metabolomics or transcriptomics, multivariate statistical analyses or soil microbiology Further, we will prefer candidates with some of the following qualifications: Teaching and
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of metabarcoding data, plant metabolomics or transcriptomics, multivariate statistical analyses or soil microbiology Further, we will prefer candidates with some of the following qualifications: Teaching and
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responsible for project milestones and deliverables. Teach and supervise MSc student projects For this position, experience with simulation development and coding is essential. We expect the candidate to have
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journals and conferences. Collaborating with academic and industrial partners, both nationally and internationally. Engaging in the mentorship and supervision of BSc and MSc student projects, co-supervising