44 machine-learning-and-image-processing-"RMIT-University" positions at SciLifeLab in Sweden
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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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personnel from all different sites at the NBIS retreat. Requirements You should hold at least a bachelor’s degree in computer technology, computer science, systems science or possess documented equivalent
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part of our values. For information about processing of personal data in the recruitment process. It may be the case that a position at KTH is classified as a security-sensitive role in accordance with
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, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab
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. The project explores the role of tumor-promoting inflammation in cancer progression through bioinformatics-driven, machine-learning and multi-omics analyses integrated with experimental data. Ideal candidates
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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of organisms, and how these processes respond to environmental changes. Recent advancements in plant and animal physiology have been accelerated by the use of novel single-cell and tissue analysis techniques
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part of our dynamic team, you will work closely with researchers to process large-scale biological data and contribute to advancing our data analysis infrastructure. Strong problem-solving skills
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting