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Model over that pipeline — a model that does not just generate code, but predicts the consequences of an architectural decision: total cost of ownership, unintended side effects, latency and failure
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the copan:LPJmL modelling framework (https://copanlpjml.pik-potsdam.de) to investigate the co-evolution of human land management decision-making and biophysical land dynamics. By explicitly coupling social
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(100%, E 13 TV-L, 3 years + possible extension, m/f/d) We seek a highly-motivated postdoctoral research fellow with strong expertise in cognitive computational modeling and an interest in applying
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, in particular the semantic integration of the "Preliminary Engine Architecture" tool and the GTlab framework for Large Language Models (LLMs), as well as multi-agent architectures for the automated
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research the dynamic processes of the Earth system. Our vision: “Taking the pulse of the Earth to safeguard a habitable planet.” For section 2.5 Geodynamic Modeling (department “Geophysics”), we are looking
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interpretable models of molecular disease mechanisms, with a focus on identifying proteins and pathways involved in cardiovascular disease. PhD project: Causal multi-omics modeling of disease biology We
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, the European Research Infrastructure for Modelling Human Diseases, is a non-profit organization dedicated to advancing disease understanding and treatment through cutting-edge models. Operated by a network of
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Magdeburg, Sachsen Anhalt | Germany | 6 days ago
models to detect, monitor, and predict subtle cognitive impairment and future change Supporting ongoing data collection in local and national research cohorts, including monitoring
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rigs" for components such as intake, nacelle, bypass duct as well as nozzle and mixer. Implementation & training: you prototype selected AI/ML models (e.g. PINNs, graph-based models) within
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 7 hours ago
for: Analysis of phenotypic, microscopic, PET/MRI, MALDI-MSI, and LC-MS/MS data Development of AI-based models for personalized risk assessment Validation and application of model performance using established