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test the BEE server, a GDPR-compliant, pseudonymized platform for secure geocoding and linkage of environmental and health datasets. Statistical modelling in R: Using advanced statistical packages
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coronary events and other NCDs. Statistical modelling: Conducting advanced inferential analyses in R, leveraging packages for epidemiology (e.g., survival, Epi, mgcv), spatial statistics (sp, sf, gstat), and
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machine learning. Strong proficiency with R/Python and machine learning frameworks (e.g., PyTorch, TensorFlow). Prior experience with workflow management tools (e.g., Snakemake, Nextflow). Familiarity with
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in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from
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dynamics resulting from varying compositions. An adaptive Model Predictive Control strategy is envisaged for this challenge. During the four-year doctoral programme, you will contribute to the group's R&D
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the context of type 1 diabetes. Essential Master's in bioinformatics, data science, biomedicine, bioengineering, biotechnology or related fields Programming experience in Python and/or R Excellent
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Python or R, and experience in the Linux environment Experience with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake
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, critically-thinking, self-motivated, flexible, and enjoys working in a team Desirable but not required: Programming experience, preferably in Python or R, and experience in the Linux environment Experience
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in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from
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technologies with industry (R&D centers from international companies, Flanders’ top innovating large companies and SMEs, as well as numerous high-tech start-ups). In order to support the research, IDLab created