132 computer-science-image-processing-"University-of-Iowa" Postdoctoral positions in Sweden
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Computing Science seeks a postdoctoral researcher who will work on Compilers for Linear
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Diagnostics (DCD) at JU offers three different undergraduate programs: the X-ray Nurse Program, and the Biomedical Analyst with two specializations (Laboratory Medicine and Clinical Physiology). It is a dynamic
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research unit. The division focuses on uncovering molecular mechanisms of health and disease through advanced imaging and biophysical approaches. The research group hosting this position studies Contractile
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sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
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6 Sep 2025 Job Information Organisation/Company Lunds universitet Department Lunds universitet, 009999 LUNDS UNIVERSITET, 150000 NAT Research Field Biological sciences » Biology Biological sciences
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independently and in a structured and reliable manner. Extensive experience in synthetic organic chemistry. Assessment criteria and other qualifications Industry experience will be considered a merit. Prior
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The supervisor for this position, Dr. Eran Elhaik, led the compositional genomic analyses in over a dozen sequencing consortia, whose results were published in Science, Nature, PNAS, and Genome
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/councils, EU framework program or industry. Qualifications To be eligible for this postdoctoral position, you must hold a PhD in Structural Engineering, Civil Engineering, or a closely related field, with a
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering