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Field
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About the Role We are seeking brilliant and passionate Algorithm Researchers to join our core team dedicated to advancing the frontiers of Artificial General Intelligence (AGI). In this role, you
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practical basic algorithms and data structures in practical implementation experience. High-level programming languages (e.g., Python), proficiency in multiple languages is preferred. Preferably with medical
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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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to biomedicine. The Ideker lab also supports multiple open-source software projects, some with 10K+ users. The Research Software Developer will work under the supervision of the senior members of the software
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Science Specialist will: 1) review empirical data and algorithms applied to the price, end-use, fishing effort and layer 3 databases and develop code that imputes missing data to complete gaps in
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University of Massachusetts Medical School | Shrewsbury, Massachusetts | United States | 10 days ago
addition to performing activities related to data mining, data analysis and recoveries. With increasing independence, the Investigator II is assigned to multiple provider types and serves as a senior investigator in the
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will include contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to be able to contribute in the following areas: Extend our
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network performance across multiple layers and levels of abstraction The ideal candidate will possess strong expertise in quantum communication and networking, with a solid command of both theoretical
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literature. Foundational Algorithms for AGI AGI will not emerge from scaling existing models alone; it requires a new algorithmic foundation for learning, reasoning, and adaptation. This research area is
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recognition neural networks (e.g., Tsetlin Machines, Graph Neural Networks, RNNs for time-series causal discovery, XGBoost). AI-driven heuristic search (e.g., genetic algorithms, genetic programming, simulated