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diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry
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scientific computing in high-performance computing environments are essential. Excellent written and spoken English skills are required. We are also looking for someone with experience with 3D image processing
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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to receiving your application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and
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of 3.3 billion SEK (about 350 MUSD) over 12 years from the Knut and Alice Wallenberg (KAW) Foundation. The DDLS program funds 50 high-profile young group leaders (“Fellows”), over 210 postdoctoral
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– Documented experience in large-scale data management, high-performance computing systems, GPU acceleration, and parallel file systems – Ability to communicate fluently in English, both spoken and written
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. Responsibilities include designing, performing, and optimizing experimental workflows, including tissue preparation and sectioning, antibody-based assays, and highly multiplexed immunostaining and microscopy, as
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methods. Good computer skills. Meriting Qualifications Documented theoretical or practical experience in structural biology and/or mass spectrometry. Experience in project management and communication with
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analysis and computational modelling. This position offers the opportunity to contribute to innovative experimental research within a dynamic and collaborative environment, advancing high-impact studies
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a