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Details Title Postdoctoral Fellowship in Reinforcement Learning, Probabilistic Methods, and/or Interpretability School Harvard John A. Paulson School of Engineering and Applied Sciences Department
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Classification Title Postdoctoral Researcher Working Title Postdoctoral Fellowship - Development of Innovative Airborne Communication Systems Brief Position Overview The Spectrum Lab (https://spectrum.montana.edu
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related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with transformer architectures (e.g., ViT
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Hospital, Copenhagen). The successful candidate will be responsible for designing and implementing the predictive modeling strategy of the project. This includes: Developing machine-learning prediction
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Postdoctoral Associate to begin July 1, 2026. The one-year term position is renewable for an additional year based on performance and is part of Cornell’s Active Learning Initiative . This initiative supports
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, statistics, and machine learning. We offer a full-time position with the following benefits: Flexible working conditions including negotiable part time contract. Monthly gross salary: 54 - 72 thousand CZK
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protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction