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Python, including use of data analysis libraries such as pandas and scikit-learn Experience with Large Language Models (LLMs): using APIs (e.g., OpenAI, HuggingFace), or local models (e.g., Ollama
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) on relevant tissues/organs and models You optimize sampling, marking and tissue preparation protocols You ensure the quality, traceability and initial analysis of data # Data integration & analysis You
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Institut des Hautes Études Scientifiques | Bures sur Yvette, le de France | France | about 13 hours ago
on problems of interest to the Simons Collaboration on Probabilistic Paths to Quantum Field Theory, in particular on the tensor network renormalization group for statistical physics lattice models. We welcome
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• Coupling of the release of the active ingredient and the dissolution of model clots (fibrin matrices from commercially available plasma) • Analysis of the results INPHYNI's activities are based on three main
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networks, to name but a few. The development of these systems requires realistic modeling of these propagation channels. The main difficulty lies in measuring this multi-dimensional propagation channel (time
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. To achieve our objectives, we will use cutting-edge technologies (CITE-seq, RNA-seq, Ribo-seq) and combine analysis in readily available relevant cellular models of cancer-experienced T cells, syngeneic mouse
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predictive modelling Public policy evaluation Management and analysis of survey data Software proficiency Statistical and econometric packages such as Stata, R, or Python GIS software (QGIS, ArcGIS
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. It is expected that the data obtained will ultimately make it possible to the development of a new application-oriented model. We are looking for a strong postdoctoral fellow who will be able to become
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Institut of Mathematics of Marseille | Marseille, Provence Alpes Cote d Azur | France | 3 months ago
time post-doc position starting in November-December 2025 in the A*MIDEX Chaire d'Excellence-funded project “Nonstationary Models of Biological Signals” (NOMOS), Principal Investigator Prof. Anna Dudek
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proposes to combine in situ and remote sensing data, radiative transfer models, and chemical and physical analytical methods to better understand the fundamental properties and the impact of mineral dust