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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
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equivalent), preferably within civil and environmental engineering, statistics, industrial ecology or data science with a passion for sustainability. We welcome candidates with postdoctoral experience
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data) datasets in cohorts of various ethnicities. The Di Angelantonio-Ieva group is seeking to recruit a highly motivated Postdoc in Genetic Epidemiology/Statistical Genetics. The postholder 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
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
and scenario models Experience and understanding in statistical analyses. Collaborative skills and ability to participate actively in multidisciplinary teams A fondness for taking the initiative and the
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, or landscape modelling Further, we will prefer candidates with some of the following qualifications: Teaching and supervision experience at the BSc and MSc level Interest and preferably experience in developing
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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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given significant consideration in the selection process.Essential qualifications- Completed (or near-completed) Ph.D. in economics, statistics or a related quantitative discipline by the start of
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, VUB and INBO. Profile We are looking for a highly-motivated candidate with a MSc degree in Biology, Ecology, Bio-Engineering, Environmental Engineering, Geology, Physical Geography, Earth Sciences
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, scipy, scikit-learn, pytorch, pytorch geometric, etc.). Proficiency in statistics and graph machine learning, including the ability to build and deploy models, and evaluate their performance. Software