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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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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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, articles and reports. You will then derive and compare statistical and mechanistic relationships. As the lead author, you will publish your results in scientific journals and present your main findings
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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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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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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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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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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