26 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof" PhD positions at SciLifeLab
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, each focusing on different areas within cell and molecular biology: computational biology and bioinformatics, microbiology and immunology, molecular biology, molecular biophysics, molecular evolution
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The Department of Biochemistry and Biophysics is seeking a Researcher and Head of Unit with experience in drug development for placement at the Biochemical and Cellular Methods Unit, Science for
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an international environment and is focused on animal biology. Outstanding and high impact research is conducted in broad fields, from genomics to ecosystems, nerve cells to behavior and evolution to conservation
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algorithms to detect complex structural variants in humans using long DNA sequencing reads. A structural variant (SV) is a large-scale alteration in the genome that involves rearranged, deleted, or inserted
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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to participate in relevant research projects and prepare for an international research career. Read more about the research at The Department of Chemistry – BMC at our website . Project description This project
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will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4
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Are you interested in developing computational tools and learning strategies for understanding health and disease at the microscopic scale? Would you like to be part of a research team with skilled
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ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading
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description The project focuses on studying the evolution of evolvability using computational simulations. Evidence from evolutionary developmental biology suggests that evolvability can change rapidly in