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Field
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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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, Mathematics, Statistics, or Physics, or a related discipline; You’re excited about research and you are motivated to explore the areas of differential and probabilistic programming and mathematical aspects
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Bachelor or Master’s degree in a relevant field (e.g., transportation, urban planning, geography, civil engineering, spatial science, or mathematics) Demonstrated ability to undertake high-quality research
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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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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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strongrecord of scientific productivity is preferable. The successful applicant must have a Ph.D.in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering orrelated field at the start of
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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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rerum naturalium, abbreviated to Dr rer nat) or the academic title PhD. The Department of Mathematics and Computer Science confers the academic degree of Dr rer nat. Alternatively, women can be awarded
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mathematical statistics (University of Gothenburg / Chalmers University of Technology) Prof. Mats Nilsson, pioneer in spatial genomics (SciLifeLab & Stockholm University) Integration into the national DDLS
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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