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in glasses. The topics range from materials’ deformation to machine learning approaches and we are interested in particular in complex metallic glasses. Some recent example publications are: .Phys
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, electrical conductivity of composites FEM modeling, optimization, machine learning, and evolutionary algorithms * extensive knowledge of composites and conductive composites * programming skills (MATLAB, Python) and
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Description KEY WORDS: Medicinal chemistry, “Hit to lead” – molecules optimization, Chemoinformatics, Bioinformatics, Data analysis, Machine learning, Artificial intelligence Recruitment to Laboratory
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cognitive and brain sciences, quantum computing, artificial intelligence and machine learning. The initial appointment is for two years with a possible extension for a third year depending on performance and
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of statistical data analysis methods and potential application of machine learning techniques. Good command of English (B2/C1). LanguagesENGLISHLevelGood Research FieldPhysics Additional Information Benefits
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; Development of models to describe forest condition based on environmental data and stand parameters using various statistical/machine learning methods; involvement in dissemination activities; publication
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algorithms (e.g., in quantum machine learning methods) and to develop new ones with promising practical applications. Furthermore, we intend to apply these mathematical insights to symmetry-based reductions
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• experience in working with a synthesizer (knowledge of phosphoramidite chemistry preferred) • ability to prepare the text of a scientific publication and present the results • knowledge of computer programs
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both modes of detection, at one side by means of ion-transfer voltammetry, at the other using well established methods of voltammetric analysis of dopamine on carbon. Secondly, machine learning methods