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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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, Tenured/Tenure-Track, Full Time, Faculty - Computer Science California State University, Fresno College of Science and Mathematics Department of Computer Science http://fresnostate.edu/csm/ Computer Science
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disease progression. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will
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Raman system in close collaboration with industrial stakeholders (Veridis) If the project is successful, Veridis intends to offer a follow up to continue the development. Where to apply Website https
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contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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: genetics, epigenetics, inflammation, metabolic pathology, autoinflammatory pathology, autoimmunity, arthritis, computational analysis, mathematical modeling, applied algorithms, machine learning in biology
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computer science, such as Data Structures, Algorithms, Computer Architecture, Operating Systems, Databases, Computer networks, Cloud Computing, Machine Learning, Data Science, full stack Web Development. Prior
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develop theoretical and algorithmic approaches to mitigate them. Key responsibilities include developing bias detection tools, building fairness-aware algorithms, and contributing to practical guidelines