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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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/ ) at the centra for molecular life sciences – SciLifeLab. The project takes place in collaboration with researchers at the centra with the goal of analyzing cellular processes on the nanoscale. Project aims and
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related field, with a focus on computing or data science. Additional requirements are: Significant experience in bioinformatics, genomics, computing, machine-learning, or other data science area
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therapeutic strategies that efficiently target currently hard-to-treat ovarian carcinomas. Work responsibilities The successful applicant will independently perform animal experiments with human ovarian
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applied machine learning projects in, e.g., computer vision, in close collaboration with industry partners. The position is not connected to an existing project, so the postdoc fellow will either join an
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with competent biomechanists, computational engineers, and experimentalists from Kungliga Tekniska högskolan, Chalmers University of Technology, and Karolinska Institutet.Project information: https
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you will be part of a growing research environment that meets regularly for seminars and other research-related activities. Employment information Employment: Temporary employment for 2 years with
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of bioadhesives to better predict and optimise the production process and product properties, and thus ultimately expects to enhance the efficiency of the production process in different wood and fibre-based
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lignocellulosic biomass largely depend on the plant origin as well as the separation and extraction processes, which affect their durability and stability in the final products. Therefore, there is a great demand
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grazing systems to improve the system’s economical sustainability. Tasks Perform wet chemistry analyses, manage and analyse biological data collected during grazing trials with dairy cows Author research