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approaches, including Low Impact Development (LID) practices (e.g., green roofs, rain gardens), with a specific focus on urban catchments. The research will place a strong emphasis on machine learning
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within a BSc/MSc thesis project. · Ability to effectively and reliably coordinate with the supervisor and multiple collaborators Language skills · Good level both written and spoken
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the conditions defined for admission to a PhD programme at NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree with a learning outcome
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colleagues at Public Health to evaluate the development of a Mental Wellbeing approach that is designed with and delivered by the Voluntary, Community, Faith and Social Enterprise Sector. The learning from
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similar field; expertise in programming skills and statistical data analyses, including machine learning; affinity with environmental exposure modelling and high-performance computing; strong reporting and
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interest in environmental health and Exposome research; expertise in programming and quantitative data analysis, including machine learning in R/Python; affinity with bioinformatics; strong collaboration
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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tomorrow’s living environments? And how can we support mutual learning between researchers in the geo-information sciences and societal actors when engaging with an increasingly uncertain and turbulent future
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model due to the mathematical challenge of solving the multiple partial differential equations simultaneously. With the support of the combined sponsorship from the university and industrial partner
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to learn unfamiliar tools as needed (e.g. GitHub, APIs, new libraries). Familiarity with econometric techniques, especially panel data methods. Clear, concise written and verbal communication skills. Ability