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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! Be
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Intelligence Learning department of the Computing and Data Sciences (CDS) directorate at Brookhaven National Laboratory (BNL) invites exceptional candidates to apply for a post-doctoral research associate
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. The postdoc will actively explore how reinforcement learning techniques can be applied across a range of complex operational domains, such as energy systems, health care, and scheduling and planning. A strong
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Position Title: Postdoc Research Associate in Machine Learning Appointment Type: Post Doc/Trainee Job Description: Summary of Duties and Responsibilities: This position will involve developing
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Job related to staff position within a Research Infrastructure? No Offer Description Job description The postdoctoral researcher will work on robot learning for manipulation, exploring state-of-the-art
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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a machine learning model (foundational model) to propose protocols of sequential induction of transcription factors to generate desired cell subtypes. The project will be conducted in close
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at: Postdoc in Machine Learning for Combating Antimicrobial Resistance Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 6 days ago
]. This requires interactively defining a template per flower, and is not suited to multi-layered petals, as in case of a rose. This postdoc position is concerned with a data-driven approach that learns
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and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and