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Field
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and heart disease in children and adults with congenital defects. Research spans from preclinical and phantom work, to large multi-centre trials with the goal to improve the clinical pathway and patient
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Experience analyzing and interpreting large-omic datasets. Multi-disciplinary experience in integrating cellular and molecular mechanisms and data with phenotypic, physiological, and psychological data
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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. This creates a large loss of value of strategically valuable raw materials and waste of energy related to material, cutting tools and parts production. The PhD project will therefore focus on automating and
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Description/content BIGS DrugS was founded in the year 2010. It is part of the BIGS (Bonn International Graduate Schools ) umbrella programme for structured doctoral programmes at the University of Bonn. BIGS
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on the grid is a global challenge, with countries and companies competing to be the first to achieve it. Successful, large-scale power generation using fusion will be a major step towards achieving Net Zero and
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practical experience in data science applied to medical or population genomics or other omic demonstrate experience in analyzing large omic data be proficient in one programming language be able to work
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applied to medical or population genomics or other omic demonstrate experience in analyzing large omic data be proficient in one programming language be able to work independently and in a structured manner
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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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and epidemiological characterisation of cardiovascular risk among people living with T1D, using multimodal data in the large SFDT1 cohort study. This work will lay the groundwork for developing novel