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during surgery or endoscopic exploration. This postdoctoral position aims at developing innovative deep learning algorithms to help histology classification. Both classical histology based on hematoxylin
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria PhD in computer science, deep learning, or data science. Experience with multimodal models for biological data. Website
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projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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POSTDOCTORAL SCHOLAR Requisition # 4568 Position Basics Advertising Ends on:Tuesday, August 18th, 2026 Advertising Started on:Tuesday, March 31st, 2026 College:Carver College of Medicine
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atmospheric perturbations, and improving performance under realistic operational conditions. Main activities include: • Designing and developing deep learning models to correct wavefront sensor nonlinearities
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. To apply, visit https://northeastern.wd1.myworkdayjobs.com/en-US/careers/job/Boston-MA-Main-Campus/Postdoctoral-Research-Fellow--Moderna---Clinical---Quantitative-Pharmacology_R139074 Copyright 2025
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approaches to remove atmospheric particulate (e.g., PM2.5) pollution. The math-based subgroup focuses on the use of deep learning and generative AI to address critical problems for the electric grid and broad