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advantage Experience with statistical analysis, regression, or uncertainty-aware modelling Proficiency in scientific programming, particularly in Python (experience with scientific computing and ML libraries
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that can be implemented across multiple studies within research networks. Support quality assurance processes to ensure consistency in how economic data are captured, coded, and reported across participating
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data science techniques to model and classify population health risk and disease dynamics at multiple spatial and temporal scales. The PDRA will lead the development of novel approaches for managing
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language such as Python, MATLAB, R or NCL. Proven ability to work both independently and as part of a team. Experience of disseminating findings through scientific publications and conference presentations
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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interest in Earth system and climate change sciences; hands-on and curiosity-driven, and ability to work independently and collaboratively; affinity with object-oriented coding (preferably Python), GIS and
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knowledge and proven capacity of data analytics and machine learning. *Excellent programming in Python, R, SQL. Have experience with tools such as Google analytics, AWS, Looker, Tableau, or similar
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cost of captured CO2 Conducting user-economic analysis to evaluate the cost implications for data center services Developing business cases under multiple socio-economic carbon price scenarios Assessing
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expertise and a strong publication record utilizing advanced statistical modeling and missing data techniques, specifically multiple imputation. Strong foundational knowledge of pediatric health and clinical
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environment is a fundamental human right. We believe that ensuring a prosperous global future depends on the ability to support local people and communities everywhere. By working in and across multiple