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, applying advanced modeling techniques and analyzing large-scale datasets to contribute to healthcare policy decisions. The PhD project will be supervised by Dr. Nora Franzen and Professor Maarten J. IJzerman
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the model plant, Arabidopsis thaliana. The PhD candidate will employ molecular biology tools to follow circadian gene expression in Bacillus subtilis as it colonizes the plant root. This work will be carried
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) and experience in applying machine learning or AI techniques in research. You have good quantitative research skills (e.g., survey data, experiments, web-scraping, regression models). Willingness
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selection lines in the model insect Tribolium castaneum. Compose an integrative overview of genes and developmental pathways involved in temperature-dependent egg development to determine universal targets of
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data into models and ensure knowledge transfer to other work packages (WPs) and stakeholders. Communicate research findings through scientific publications, public engagement activities, and
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assessment tools for OSH professionals. In this project, we aim to develop a 'Biological Exposome' risk model for the workplace using a layered approach, moving from qualitative to quantitative risk assessment
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the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics its processing capabilities but also its adaptability, leveraging early
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As urban populations grow and energy demands rise, urban-scale energy system modelling is critical for reducing emissions, enhancing resilience, and integrating high shares of renewable energy
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this NWO summit EMBRACER project at the forefront of polar research. You will explore Arctic sea ice decline and ocean warming using satellite data and coupled modelling tools. Collaborate with
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), we aim to close this gap, by developing AI models and tools for tabular data, to help organizations, of any size, domain, and level of data literacy, get insights from structured data, efficiently