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- Institute of Biochemistry and Biophysics Polish Academy of Sciences
- Adam Mickiewicz University, Poznań
- Bydgoszcz University of Science and Technology
- Center for Theoretical Physics PAS
- Institute of Low Temperature and Structure Research Polish Academy of Sciences
- Institute of Physical Chemistry, Polish Academy of Sciences
- Polish Academy of Sciences Institute of Medical Biology
- Poznan University of Technology
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- Wrocław University of Science and Technology / Faculty of Information and Telecommunication Technology
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twins, human-centric systems, robotics PhD-E: Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection. PhD grantors: University Padova (IT) & Poznan University of Technology (PL
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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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Wrocław University of Science and Technology / Faculty of Information and Telecommunication Technology | Poland | about 2 months 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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to work in a group, curiosity, and motivation to learn. - Willingness to work in interdisciplinary and international teams. - Fluency in written and spoken English. Additionally appreciated: - Experience in
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disabilities; flexible working hours; funding for language learning; co-financing of training and courses; additional days off for education; life insurance; pension plan; savings and investment fund
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Institute of Low Temperature and Structure Research Polish Academy of Sciences | Poland | 5 days ago
. The resulting data will be used to train a machine learning algorithm to predict the pressure-induced variation in the luminescent properties of phosphors co-doped with Cr3+ and Mn4+ ions based on the structural
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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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, 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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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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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