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Wrocław University of Science and Technology / Faculty of Information and Telecommunication Technology | Poland | about 1 month ago
include creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools for semantic search
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data integration data quality data analytics programming languages (SQL, Python, Java) Complementary IT skills: machine learning image recognition sensor technologies robotic technologies
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, independence, and a collaborative spirit Prior experience in cancer biology, meiosis, or proteomics is a plus but not required—enthusiasm and a willingness to learn are highly valued. 📝 Join us This is a unique
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projects in the laboratory. Learning and designing new technologies. Perform cell culture, including isolation of primary cells. Participating in laboratory activities, including laboratory meetings and
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properties through tuning of concentrations and types of viscosity modifiers and superplasticizers, deep learning modeling of parameters of cement composites. The project is realized at the Bydgoszcz
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substrate–catalyst–conditions combinations). The resulting experimental dataset on catalyst activity (TON, TOF) and selectivity will be used to develop predictive machine-learning models that enable accurate
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patterns across multiple annotation types. The core aim is to generate new scientific insight by associating LCRs with their functions through a combination of expert curation and modern machine learning
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research centre in Poland.Research conducted at the Institute focuses on issues directly related to health protection and improving the quality of life. The Institute's main mission is to learn
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of biological databases, algorithms and pipelines; experience in working with phylogenetic/ genomic/transcriptomic/systems biology tools will be a bonus; being well organized, eager to learn and ready to
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the project is the development of AI-based pipelines for detecting, segmenting, and classifying lichen communities. Convolutional neural networks (e.g., U-Net, DeepLab) and machine-learning algorithms (e.g