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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
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., M.D., D.V.M.) Preferred Qualifications:. Detail-oriented, very well organized, and approach laboratory procedures with critical thinking. Strong initiative and eagerness to learn. Outstanding problem
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data-driven methods (optimisation, generative AI, agent-based modelling, machine learning). Our work provides decision support for policy makers, industry stakeholders, and researchers by delivering
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, etc.), and data-driven methods (optimisation, generative AI, agent-based modelling, machine learning). Our work provides decision support for policy makers, industry stakeholders, and researchers by
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manufacturing, health and transportion: Interperability of systems Data Management Big data analytics AI and Machine Learning Experience in the organization of international events such as workshops and
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Again – AI-driven Voice Restoration for Pathological Speech• Machine Learning and In Silico Modeling of Sex Differences in Temporomandibular Joint Function• AutoPiX – Machine Learning for Imaging-Based
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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engagement, or programming--are encouraged to apply, with opportunities to grow in other areas through collaborative mentorship and team-based learning. As part of Cornell University, a world-class research
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professional development opportunities and strive to meet each individual’s development and well-being goals as much as possible. As an associate researcher with expertise in the field of machine learning within