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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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experience with process modeling with Aspen Plus Demonstrated experience with statistical analysis (i.e. sensitivity or uncertainty) PhD degree in chemical engineering or related field Preferred Qualifications
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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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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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2 Mar 2026 Job Information Organisation/Company Ecole Centrale de Lyon Research Field Chemistry Computer science Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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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
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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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Georgia College & State University (GCSU) is the state's designated public liberal arts university, where students learn the essential skills to compete in a fast-paced and technology-driven global
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simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative
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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