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Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired, method-driven theory to application-driven research. Please find more
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hydrologic and hydraulic models (e.g., WRF-Hydro, HEC-RAS, OpenFOAM, GSSHA, Delft3D, EFDC, etc.). Data Engineering & Computational Workflows – 35% Curate, preprocess, and analyze large environmental datasets
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Apply now Job no:537640 Work type:Full Time Location:Sydney, NSW Categories:Information Technology, Analyst, Cyber Employment Type: full time continuing role Specialist II, Security Engineering
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
. This involves theory but also the integration of observational information into models through data assimilation and model inversion. In this domain as in many fields of applied science, researchers face high
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, Autonomous and Interactive Systems, and Global Sustainability Engineering. Project Overview The AI Pathologist project is an interdisciplinary initiative aimed at developing an advanced AI-driven diagnostic
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), regulatory science, pharmacometrics, and real-world evidence (RWE). The successful candidate will develop AI-driven systems to support regulatory document intelligence, automated pharmacokinetic modeling, and
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UPOs PhD enrolment: Université Paris Cité DC15: Hybrid machine learning models for data-driven bioprocess optimisation PhD enrolment: University of Padua Eligibility Requirements: Doctoral Candidates
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goal is to implement AI-driven solutions in textile engineering, fashion and textile design, textile management and business-oriented IT, with the aim of promoting a green transition in the textile and
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an emphasis on technology, data science and the humanities. The Nutrition, Metabolism and Health Programme is addressing one of the world’s most pressing healthcare issue: Over nutrition driven chronic diseases
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unique biological systems. To achieve this goal, we are mining novel biological systems from databases using AI-driven tools, characterizing their functions through biochemical analysis, engineering them