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Field
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for candidates with a strong computer science background, such as algorithms, machine learning and data science. Key Responsibilities Develop, implement, and evaluate machine learning and deep learning models
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equations (SDEs) are widely used to model time-evolving phenomena in finance, biology, and social dynamics, the underlying data is often highly sensitive. This project tackles the intersection of complex
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during the appointment. Diagnosing and analyzing the numerical challenges related to the narrower data width Devising and evaluating novel techniques to exploit the reduced precision hardware Incorporating
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multidisciplinary and highly collaborative research team and will lead research projects tailored to the candidate’s interest. The candidate will also have numerous opportunities for career and professional growth
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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with 2D numerical modeling of river hydraulics as evidenced in application materials. Note: To be appointed at the Postdoctoral Researcher title, it is necessary to have the PhD conferred at the time of
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
code development or open-source contributions, polymer chemistry, and mathematics, modeling, or numerical methods. An established record of research productivity is highly desired. Special Physical
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mathematical tools and financial models for capturing complex market dynamics . Assets, principal investigator Prof. Dr. Ciprian Andrei Tudor. The position is for a fixed term until June 30, 2026. Candidates
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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heterostructures. This position offers opportunities for collaborative theory development, advanced numerical modeling, and participation in a vibrant, multi-institutional research environment. Regular joint