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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month ago
modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of machine learning, uncertainty quantification, and Bayesian modelling. They will provide complementary expertise to bridge agentic AI with real-world impact. What We Are Looking from You Background in
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 6 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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implementing models that integrate ecological dynamics, species traits, phylogenetic trees, and economic discounting; ● Devising Bayesian or POMDP frameworks to handle uncertainty about species interactions
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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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learning, evidence synthesis in public health and statistical genetics and genomics. We are recognised for our strength in Bayesian inference applied to biomedicine and public health. The MRC Biostatistics
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 29 days 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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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