442 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" positions in Belgium
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and automating the acquisition of high-quality training datasets for machine learning models. Provide training to students on new technologies, protocols, and best practices. Support grant applications
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processes in the team (e.g., setting goals, coaching, evaluation). You create a strong team atmosphere and foster opportunities for knowledge sharing and cross‑learning. You interact closely with your peers
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-guided machine learning. You are quick to assimilate information and capable of independent research. Experience in the pharmaceutical sector is an advantage You speak and write English fluently. You are
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manipulation of fear and reward learning. This position is part of a recently funded, large-scale and innovative research program, aimed at creating new treatments for negative symptoms, among the most
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. Machine learning will assist in artifact correction, segmentation, and material classification. By combining experimental imaging, simulation, and data-driven interpretation, this approach will deliver high
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Research Council (ERC) Starting Grant https://www.kuleuven.be/english/research/EU/p/he/p1/erc/IonFracMem ) aims to address this challenge by developing novel membranes that combine fast throughput with
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ESM Item Repository (https://esmitemrepositoryinfo.com ). Building on ongoing methodological and meta-science work in the CCP and CMPO, this project will develop and psychometrically validate gold
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Website https://www.kuleuven.be/personeel/jobsite/jobs/60606914?hl=en Requirements Research FieldComputer scienceEducation LevelPhD or equivalent LanguagesENGLISHLevelBasic Research FieldComputer science
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environmental thresholds for mangrove establishment and coastal protection. This computer modelling step may be elaborated by the PhD student or another post-doctoral researcher working on the project, depending
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. More information can be found on our website: https://www.b-phot.org . The candidate will be supervised by Prof. Francis Berghmans, and co-supervised by Dr. Sidney Goossens and Dr. Sergei Mikhailov