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to trade in production. We don’t believe in “one-size-fits-all” modeling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep
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dimensional information, classification and/or deep learning methods may also be developed. In addition, the complementarity between the different data sources used (particularly between aerial LiDAR data and
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physical and chemical properties of aerosol particles and clouds. Current research focuses on related but different areas of aerosol science and covers the whole size spectrum from the nano
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properties of aerosol particles and clouds. Current research focuses on related but different areas of aerosol science and covers the whole size spectrum from the nano- to the microscale. We are looking for a
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different backgrounds and with those who may have different perspectives. Outlined below are the primary focus areas for this position. However, the expectation is that as OIRA's portfolio expands
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projects at different stages, with different types of design, levels of involvement, stakeholders, reporting requirements, etc. Strong interpersonal skills, including tact, diplomacy, and flexibility as
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, Skills and Experience Broad knowledge of statisticsSkills in programming languages such as R and/or Python Experience of applying statistics to solve complex real-world problems Ability to handle a diverse
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skills; hands-on experience in programming languages, such as C++, Python, …. • You have strong analytical skills to interpret the obtained research results. • You are a team player and have strong
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the laboratory's past and ongoing work within the context of AI-guided Design, Inverse Design, and Optimization across different application domains. In particular, we are developing scientific research
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evaluation of different glaciation histories with a focus on the mid Holocene and the Little Ice Age Numerical GIA-modelling with advanced 3D codes, evaluation and validation of results in collaboration with