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. However, current estimates of methane emissions from inland waters to the atmosphere are highly uncertain because of limitations in long-term observational data and modelling methodology. In this four-year
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Qualities:You are a computer scientist, a computational biologist or a computational chemist with proven expertise in implementing machine learning methods in Python. You write or have written your master's
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framework and execution of projects > Understanding of financial products, market dynamics, and microstructure > Low-level computer languages like C++ or Python, Java, etc.; awareness of strength in
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in applying causal estimation methods in healthcare. You will have the opportunity to work on a range of projects within your PhD including a collaborative initiative funded by the Innovative Health
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work will include: analysing satellite data and Lagrangian tracking to estimate how much sea ice has been exported from the Arctic over the past decades; studying how heat from the ocean contributes to
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have long-term consequences for the enslaved people and their freed descendants? The project will apply advanced empirical methods (e.g. structural estimation) in finance and economics to study these
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be submitted in one single pdf file): • A detailed CV (resume); • A letter of motivation (approximately 1 page), including an estimated starting date; • A transcript of BSc and MSc grades; • A sample
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statistics and computer languages, like R; the ability to work independently as well as in a team. We offer A contract (36 hours per week) for a period of one year, to be extended with three more years after a
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Institute). Qualifications We seek excellent students with a strong background in cosmology, astrophysics, physics, mathematics and/or computer sciences, who seek to obtain a Joint-PhD degree from
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companies. Since the estimation of spatial and network models is intricated from an econometric point view, this position provides you with the ideal opportunity to both develop strong theoretical and