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. Desired qualifications: Strong theoretical and methodological capacities in statistics Documented expertise in computational methods and experience with R or Python programming Experience in Bayesian
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background in statistics (a minimum of 60 ECTS in statistics). Knowledge in programming skills (e.g., R, Python). Candidates without a master’s degree have until June 30, 2026 to complete the final exam
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, Python, JavaScript, Ruby) for developing interactive, data-driven visualisations. Strong collaboration and communication skills, with the ability to convey technical concepts to diverse audiences in
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prompts Develop predictive models for sepsis, deterioration and ICU outcomes Create reproducible analysis frameworks using R/Python, GitHub, Quarto or R Markdown Produce real-time dashboards for ICU
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modelling reduced‑order or low‑order modelling scientific programming (e.g. Python, MATLAB, etc.) You should be able to work independently and collaboratively, communicate your research clearly, and
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learning models applied to material modeling. Proficiency in programming languages, such as Python, MATLAB, Julia, and C++, and molecular dynamics programs, such as LAMMPS, to predict mechanical/electrical
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modelling reduced‑order or low‑order modelling scientific programming (e.g. Python, MATLAB, etc.) You should be able to work independently and collaboratively, communicate your research clearly, and
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environments such as R, Java, Python, C++; Ability to communicate statistical concepts and data analysis interpretations to the group; Experience in genetic analysis of environmental exposure risk factors
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with omics data analysis, biostatistics, and image analysis tools. Strong programming skills (R, Python) and knowledge of relevant databases and pipelines. Candidates with peer-reviewed publications
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, math, statistics, and/or computer science Experience with programming, data science, and geospatial analysis (especially R, Stata, Julia, MATLAB, or Python) An enthusiasm for empirical research and an