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become a life-saving option for advanced cancer patients. However, only a minority of patients develop a durable response. Many researchers are investing efforts to understand the complexity of anti-cancer
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-assembly on a structural level, and correlate this with in vitro functional activity. At AstraZeneca, the student will be integrated into the Data Science and Modelling department within the Pharmaceutical
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project: Computational methods for complex SV detection using sequencing data Main supervisor: Kristoffer Sahlin, ksahlin@math.su.se . Co-supervisor: Adam Ameur, adam.ameur@igp.uu.se . In the Department
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aims to build predictive and physical binding models of protein – DNA interactions using high-throughput and quantitative biochemical binding data across hundreds of thousands of sequence variants
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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microtumor models. This work addresses a critical knowledge gap in cancer immunobiology and supports the development of more accurate disease models. Duties The main duty for a doctoral student is to devote
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rate, and virtually nothing is known about a putative connection between these mutation rates. Using several Drosophila melanogaster model systems, in combination with quantitative genetics, experimental
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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. The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a
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. The project revolves around developing Traident – a new method to resolve the species origins and compositions of complex RNA sequence data. This will extend Kraken2 with analyses of ribosomal RNA and microRNA