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- University of Warsaw
- Gdańsk University of Technology
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- University of Warsaw: Faculty of Mathematics, Informatics and Mechanics
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- The Tadeusz Manteuffel Institute History of the Polish Academy of Sciences
- Wrocław University of Science and Technology
- Wydział Matematyki Fizyki i Informatyki UG
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possess knowledge and skills in computer science, particularly in the areas of algorithms and data structures, databases, distributed databases, data warehousing and analytical processing, knowledge
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surrogate models. The method employs modern posterior sampling algorithms, using measurement data. The developed tools will enable faster and more accurate reconstruction of past and future emergency events
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the Generative Flow Network (GFlowNet) algorithm. We plan to further enhance this algorithm to consider the shape of biological binding sites and incorporate modules for optimizing physicochemical properties
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automation and simulation-driven optimization of high-frequency systems using machine learning * development of optimization algorithms and numerical modeling procedures * development of simulation models
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on are: • approximation algorithms in QIT (e.g. ground state energies); • symmetry- and size reduction of polynomial optimization problems; • characterization of quantum codes and quantum capacities
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analysis algorithms will be used to assess how different neutrophil subpopulations directly and indirectly kill tumour cells, and how this behaviour is influenced by other cells in the tumor microenvironment
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systems * knowledge of modern artificial intelligence algorithms * practical experience in implementing IT services using artificial intelligence technologies * experience (minimum 5 years) in teaching
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for the design and the benchmarking of algorithms tailored for photonic quantum computation. The outcome of the project will be the assembling of three prototypes: ● QSPACE, machine encoded in spatial modes and
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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