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including high-impact scientific publishing, and collaborative research with international teams. Who we are looking for Requirements MSc degree in Computer Science, Data Science, Machine Learning, or a
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implementation in Fire Dynamics Simulator CFD code Experimental validation of simulations Machine learning for accelerated evaluation of radiative properties The doctoral degree will be awarded upon successful
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collaborate with partners at ELLIS Institute Finland. Target publications at top-level AI, ML, and NLP venues. Who we are looking for Requirements Ph.D. in Machine Learning, Natural Language Processing
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, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and
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foundation in cybersecurity and adversarial machine learning. Excellent analytical and problem-solving skills. Good communication skills in English (written and spoken, e.g., with a valid International English
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international collaborations in multi-disciplinary research ranging from the development of data analysis and machine learning methods to applications in omics research. Researchers in Finland have access
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and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive international collaboration with
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of quantum walk algorithms, variational quantum algorithms and their optimization, adiabatic quantum computation, and quantum machine learning. Theoretical and applied research into the capabilities of quantum
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particularly value experience in artificial intelligence, machine learning, and data-driven systems as well as strong programming and modelling skills (e.g., Python, PyTorch, MATLAB, or R). Experience in process
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excellent study records in Electrical Engineering, Electronics, Microelectronics, Computer Engineering, or a closely related field, completed by the start of the position Have a solid background in digital