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structured training and supervision of more than 1,500 doctoral candidates in mathematics, natural and life sciences. Working on research projects towards their doctorate, the students are supported in
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sometimes). Compulsory "primer" (foundational) courses (programming, statistics, bioinformatics, biophysics) are planned as intensive courses in the period March to July. Soft skill courses (Good Scientific
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city size framework into dynamic land use–transport interaction (LUTI) models to enable scenario-based forecasting and planning under different infrastructure and policy conditions. Understanding
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the interface between different scientific disciplines including ecology, evolutionary biology, mathematics and statistics, informatics, economics and social sciences. We aim to apply advanced statistical and
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Honours degrees in the following disciplines, or with equivalent research or work experience will be favourably considered: Computer and Data Science; Applied Mathematics and Statistics. Number
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to metocean statistics and development of software packages related to the generation of said statistics. This work amounts to 25% (one year) of the total project period and allows the PhD project to run over a
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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to 1,500 EUR per month. Academic admission requirements Master's degree or equivalent in the life sciences, mathematics, computer sciences, statistics, biophysics, or a related field Language requirements
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degree (PhD equivalent). Outstanding (top 10%) students holding a Bachelor's or Master's degree in economics or related fields (e.g., mathematics, statistics, business administration, accounting, and
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methods, such as statistical methods and methods for data collection. The GSBS provides coursework in the respective fields. Interdisciplinary courses are taught by lecturers from different fields and