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on “ Integrating AI into Aquatic Ecosystem Models to Decode Ecological Complexity ” funded by Villum Fonden. Within that project, the focus is on exploring novel ways to infer information from environmental data
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, structured data for studying norm evolution in real time. Comparative work across disciplines will complement these analyses. This postdoc will have the opportunity to work at the intersection of Science
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar Department: Arts and
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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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designing/programming experiments, recruiting/running participants, developing and using computational modeling approaches (Bayesian, RL, neural networks) to analyze behavioral and neuroimaging data
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make a difference in the world! Position Information Postdoctoral Research Associate in Agricultural, Animal, Rangeland, or Environmental Sciences Location: Texas A&M AgriLife Research, Temple, Texas
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of the appointed researcher is - jointly with the research team - to design and conduct quantitative research, mostly on longitudinal register-based data on autoimmune diseases. Additionally, the researcher is
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on patient perspectives and aims to understand the information older people need about the harms and benefits of prostate specific antigen (PSA) testing (ProsDetect II). The second project addresses challenges
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project is supported by a British Academy Global Professorship awarded to Sian Halcrow. The aims of the project are Assay a wide range of collections, establishing information on acquisition and origin