34 machine-learning "https:" "https:" "https:" "https:" "https:" "Helmholtz Zentrum Geesthacht" research jobs at UNIVERSITY OF HELSINKI
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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules
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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules
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and machine learning. We focus on inductive logic programming (ILP), a form of inductive program synthesis which learns logical rules from data. The focus of this position is to develop ILP/program
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about micronutrient content, intake, digestibility and bioavailability from plant-based diets. Part of the PhD study is planned as external stay at Valio (Helsinki, Finland) for one month to learning
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micronutrient content, intake, digestibility and bioavailability from plant-based diets. Part of the PhD study is planned as external stay at Valio (Helsinki, Finland) for one month to learning legume
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the research environment: Faculty of Agriculture and Forestry, University of Helsinki https://www.helsinki.fi/en/faculty-agriculture-and-forestry Viikki Campus https://www.helsinki.fi/en/about-us
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intelligence, 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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, University of Helsinki https://www.helsinki.fi/en/faculty-agriculture-and-forestry Viikki Campus https://www.helsinki.fi/en/about-us/campuses/viikki-campus Careers at the University of Helsinki https
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facilities, and opportunities for professional development (https://www.helsinki.fi/en/about-us/careers ). YOUR PROFILE PhD in biology, mathematics, or a related field Strong background in mathematical
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-effectively predicting the rate of massively multicomponent organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning