34 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" Postdoctoral positions 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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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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-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
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the University of Helsinki and living in Finland, please see https://www.helsinki.fi/en/about-us/careers . A diverse and equitable study and work culture is essential to us. That is why we do our best to promote
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organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning and artificial intelligence methods, targeted validation
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volumes of audiovisual data is essential. The appointee must have solid skills in programming and working with libraries for training and using machine learning models. Previous experience in managing large
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pension fund, a generous holiday package, sports facilities, and opportunities for professional development (https://www.helsinki.fi/en/about-us/careers ). Required qualifications PhD (or near completion
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the Neuroscience Center in the University of Helsinki (see: https://www2.helsinki.fi/en/researchgroups/synaptic-plasticity-and-development ).The research interests are focused on functional maturation of neuronal
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Finland. More information here: https://www.helsinki.fi/en/about-us/careers/welcome-finland-information-arriving-staff How to apply The application must be submitted by 22 January. A round of interviews
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environments. Willingness to continuous improvement based on constructive evaluation, self-reflection and learning. We offer to join a group tackling research questions in crop physiology, soil science, crop