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: Develops advanced Agro-geoinformatic algorithms for monitoring and predicting the conditions of crop, pasture, and their environment with advanced remote sensing and geospatial technologies; Develops and
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and prioritize impactful software solutions and guide the team in developing creative, robust approaches to evolving research challenges. Apply AI/ML algorithms to domain-specific software engineering
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Associate to focus
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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candidates will be required to fund the difference between the home fees and international fees. Overview Are you interested in developing Brain-Computer Interface technologies to control brain stimulation in
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | about 9 hours ago
of synonymous variants in therapeutic proteins using integrated computational and experimental approaches. A central component of the project involves applying and developing advanced bioinformatic tools to model
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
the replicator equation. The candidate(s) may also be required to develop computational and algorithmic platforms to link models to biological data. The project integrates dynamical systems, graph theory, linear
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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RAP opportunity at National Institute of Standards and Technology NIST Development of New Computational Methodologies for Molecular Simulation of Soft Materials Location Material Measurement
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areas include the development of interpretable and trustworthy algorithms for Scientific Artificial Intelligence and active learning, integrating FAIR data management practices throughout the research