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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g
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research in neuro-symbolic AI, with a focus on using generative and agentic AI, as well as AI standards to create trustworthy information resources. This includes the design of algorithms, tools, and process
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under the supervision of Professor Rachel Humphris. They will lead in-depth ethnographic fieldwork in the Netherlands, undertaking interviews and participant observation to trace how welfare algorithms
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AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms for process industries (e.g., chemical, pharmaceutical, materials, energy
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self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
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interaction and/or surface flux computation, including familiarity with bulk flux algorithms and observational QA/QC procedures. Experience with processing, analyzing, and interpreting multi sensor
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a diverse team of biological and chemical scientists Experience with high performance computing environment (HPC) / cluster job submission Knowledge of statistical methods, data science algorithms
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microscopy, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand
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, Dr. Nikolaos Paterakis, and Prof. Dr. Valentin Robu. Where to apply Website https://www.academictransfer.com/en/jobs/358068/postdoc-in-ai-for-the-electrici… Requirements Specific Requirements
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for real-time human data processing in interactive settings. Technical expertise in areas such as electrophysiological recording, VR paradigm design, closed-loop algorithm development, or clinical