884 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" positions in Sweden
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identification and machine learning is a merit. What you will do Perform research, developing your own scientific concepts and communicating the results verbally and in writing Take courses at an advanced level
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position within a Research Infrastructure? No Offer Description Description of the workplace Within the Centre for Analysis and Synthesis (https://www.cas.lu.se/ ) at the Department of Chemistry, we conduct
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assays, complemented by mass-spectrometry-driven chemical profiling and machine-learning-supported multivariate analysis. Where relevant, CRISPR-Cas-based genetic perturbations in mammalian cell models
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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services can be found at: https://www.uu.se/forskning/snpseq and https://ngisweden.scilifelab.se/ We are proud to deliver high-quality data and are accredited by SWEDAC as a testing laboratory under the ISO
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-quality educational programs in Computing Science, we are now seeking a PhD student with a focus on Computer Security. The Department of Computing Science has been growing rapidly in recent years, with a
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practical skills in the field of data science, especially. multimodal data analysis. Experience on image processing (especially on MRI data) via machine learning. Programming skills (e.g., Python
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More about us Umeå University: http://www.umu.se/en/ Department of Molecular Biology: www.umu.se/en/department-of-molecular-biology/ Sixt Lab: http://www.sixtlab.org/ Laboratory for Molecular Infection
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that are commonly used today. Using the improved noise models, machine learning methods will be used to enhance the segmentation of EEG data into auditory signal and background activity allowing for refined control