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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 8 days ago
professional track record, proven experience on students’ supervision, participation in national and international scientific projects, be committed to work in a team and be highly motivated and oriented towards
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
for individuals that are interested in pursuing a PhD in economics or finance. The chosen candidate will also gain valuable experience in the application of machine learning and Bayesian inference methods
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neural codes for visual object features (identity, position, scale, orientation) and their relation to behavioral performance. Track representational reorganization during learning of new objects through
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, allowing smaller objects to be detected further away, as well as target feature extraction, which is the stepping stone to reliable target classification at further distances. This will be the first attempt
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of the Department of Mathematics at Radboud University (Nijmegen, Netherlands), and join the research group of Laura Scarabosio, funded by the NWO Vidi programme ’Taming Frequency in Bayesian Inverse
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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a
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modelling becomes crucial for developing effective mitigation and adaptation strategies for marine infrastructure. Within the Institute of Infrastructure and Environment, we maintain a track record in the
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to improve R&D efficiency, and the influence of investors and other external actors on entrepreneurial outcomes. Our research also examines decision-making under uncertainty, including the use of Bayesian
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the study of plant-plant or plant-invertebrate interactions Experience in nematology or nematological methods Strong quantitative skills (e.g., generalized linear mixed models, permutational methods, Bayesian
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mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree