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cancer models, including cell culture and preclinical models. Our lab welcomes individuals who are eager to learn and conduct studies related to pancreatic cancer metabolism. Duties and Responsibilities
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, Applications, Architecture, Network, and Security services to develop, maintain, and enhance a secure, high-integrity hybrid enterprise storage and compute infrastructure critical to the university community
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funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number B-0037-26 Is the Job related to staff position within a Research Infrastructure? No Offer Description
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based on Machine Learning (ML) emulators have taken the weather predictions research by storm, as they run faster and use less energy than traditional approaches: numerical models based on physical
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 18 days ago
28 Mar 2026 Job Information Organisation/Company IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava Research Field Computer science Researcher Profile First Stage
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of New South Wales (UNSW) is seeking a Postdoctoral Fellow to contribute to cutting-edge research in computational acoustics, multiphysics simulation, and digital twin modelling. Working as part of
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tax monthly), with 75% of public transportation costs covered by the employer and 44 days of paid leave per year. Within the framework of the PEPR B-BEST program (https://www.pepr-bioproductions.fr
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of Engineering Systems and Services of the Faculty of Technology, Policy and Management has joined the National Growth Fund program Growing with Green Steel (GGS, https://groeienmetgroenstaal.nl/en/ ), which aims
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/11250664 https://www.jmlr.org/papers/v26/25-1161.html Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in engineering, computer science, or related disciplines (typically
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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in