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disciplines, and data science seeks to build models and extract meaningful information from large amounts of complex data. Machine learning, artificial intelligence and data-drivenness cut across all our
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care sector or in a business environment and using and teaching different types of simulation tools and artificial intelligence is considered as an advantage. Success in teaching requires good
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experience in at least 2 of the following areas: quantitative analysis, ML and Data Science, artificial intelligence (AI), innovation studies, with a strong track record. Capability to learn and develop your
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civil engineering, materials engineering, computer science or applied artificial intelligence. Related scientific publications are a plus. Excellent communication skills in English are required, and
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drug design” is led by Docent Juri Timonen, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug
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interdisciplinary and international research teams Excellent command of spoken and written English Research group The Machine Learning for Health team focuses on applying artificial intelligence to derive meaningful
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for Health team focuses on applying artificial intelligence to derive meaningful insights from large, real-world health and biomedical datasets. The team is led by Dr. Tuomo Hartonen, and is part of
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). The research plans can be checked with the Turnitin OriginalityCheck plagiarism detection software. The use of artificial intelligence (AI) to assist in the preparation of the research plan should be clearly
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communities. The particular focus is to enhance the Joint Species Distribution Modelling to meet the challenges introduced by the analysis of ecological data collected with modern technologies and artificial
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developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party