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- Center for Theoretical Physics PAS
- Institute of Fluid Flow Machinery Polish Academy of Science
- Institute of Physical Chemistry, Polish Academy of Sciences
- Lodz University of Technology
- AGH University of Krakow
- Jagiellonian University
- The Franciszek Górski Institute of Plant Physiology Polish Academy of Sciences
- Warsaw University of Technology
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Field
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. Scientific and Technical Competencies: • Strong background in machine learning, deep learning, and time-series modelling, with engineering applications. • Experience in prognostic modelling (e.g., RUL
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graphics. Classical representations are relatively easy to render, while being difficult for generative machine learning models. A recent breakthrough in this area is the Neural Radiance Field (NeRF) and
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infrastructure (e.g., turbine components). Research on advanced deep learning techniques, including architectures based on GRU, LSTM, attention mechanisms, and hybrid models. Implementation of real-time predictive
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• At least intermediate knowledge of cyber security • Knowledge of programming tools and technologies • Knowledge of data analysis tools • Knowledge of basic and advanced machine learning • Basic
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• At least intermediate knowledge of cyber security • Knowledge of programming tools and technologies • Knowledge of data analysis tools • Knowledge of basic and advanced machine learning • Basic
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& Compiling: Circuit optimization, co-compilation, and error-correction-aware resource minimization. Generative Models: Exploring quantum advantage in generative machine learning, specifically hybrid approaches
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., APIs, web scraping), and/or with experience in applying at least one advanced analytical technique, such as topic modeling (LDA, STM), sentiment analysis, social network analysis (SNA), machine learning
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., computational learning theory, expressiveness of transformers and other models, xAI, formal methods) or equivalent; willingness to conduct research on artificial intelligence/machine learning, combined with
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energy consumption in information processing and machine learning (e.g., arXiv:2308.15905); Quantum phenomena in information processing: exploring how quantum effects can be utilized to process information
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on machine and deep learning methods for analyzing the heterogeneity of microbiota and inferring activities of biological pathways. The Institute provides an international and interdisciplinary research