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processing, machine learning, and optimization theory. Strong verbal and written skills in English. Excellent analytical and problem-solving skills, and capacity to pursue independent research as
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. Qualifications Applicants must hold a PhD or equivalent qualifications in a relevant field, such as Child-Computer Interaction, Human-Computer Interaction, Learning Sciences, Educational Technology, Computer
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 6 days ago
) Optimization and parameter identification methods Data-driven modeling and machine learning Physics-Informed Learning (or hybrid modeling approaches) Handling and analysis of large-scale datasets (e.g., mobility
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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks
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publication record in sensing systems, mobile health, or HCI. Experience with signal processing, machine learning, or embedded systems is a plus. Carnegie Mellon University is an equal opportunity employer. It
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hemocompatible coating strategies to improve membrane–blood interactions. - Model and optimize membrane performance using computational tools, machine learning, and artificial intelligence Work Plan - Synthesis
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Union within the project “A Comprehensive Trustworthy Framework for Connected Machine Learning and Secure Interconnected AI Solutions (CoEvolution)”, - CUP F23C24000210006 – selection code: ipd_10D_0426_09/IINF
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with causal inference methods or machine learning approaches Demonstrated experience in scientific writing and publication Ideal for candidates who: Have recently completed (or are near completion of) a
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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computing, machine learning for hardware design, integrated circuit design, or hardware–software co-design. Experience with semiconductor design tools, circuit/system modeling, or large-scale hardware design projects