238 computer-science-quantum-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ" positions in Belgium
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applications from candidates (m/f/x) with: Educational background A Master’s degree in artificial intelligence, computer science, data science, statistics, engineering, applied mathematics, economics, sociology
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engineering, and have expertise in building camera systems and computer vision. This role also involves working closely with the other members of the team on projects related to plant phenotyping (assessing e.g
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to apply plant biotechnology for applications in the Global South Welcome but not required Experience in bio-informatics Interest in automated phenotyping Key personal characteristics You are enthusiastic
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engineering, industrial engineering, mathematics, engineering, computer science, artificial intelligence). Strong study results are an asset. A strong interest in scientific research in machine learning and AI
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hold or will have obtained by the time you start work, a Master’s degree in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, Energy Engineering, or a related field
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and international projects in IRiSC, including proposal preparation, reporting, and coordination with external partners Foster collaborations across disciplines - in particular between computer science
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/ Computer Science, Mechatronics / Mechanical or Electrical Engineering, or related fields in Engineering, Computer Engineering or Applied Mathematics Programming Skills: Programming Experience with Python, C/C++, ROS
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of obtaining a PhD within a period of 48 months. These scholarships are only awarded within the framework of the planned cooperation with GUGC ('Ghent University Global Campus' in Korea) or the thematic science
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The Faculty of Engineering, Department of Applied Physics and Photonics, Brussels Photonics (B-PHOT) research group at the Vrije Universiteit Brussel (VUB) is looking for an excellent PhD candidate
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working on nonlinear and multiphoton optical spectroscopy and microscopy for molecular and materials characterization. The project is part of the broader MIP research programme across KU Leuven (Leuven and