8 machine-learning-phd uni jobs at Ghent University

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  • Ghent University | Belgium | about 17 hours ago

    . You have excellent computer science skills (python, git, linux, ROS, etc.) . You have hands-on experience with machine learning frameworks such as PyTorch. You have strong analytical skills to interpret

  • Ghent University | Belgium | about 17 hours ago

    strong background in wireless and mobile networks, as well as machine learning, ideally with exposure to Reinforcement Learning (RL) or decision-making agents. You have an interest or background in network

  • Ghent University | Belgium | 22 days ago

    validate innovative methods for mapping soil compaction at the field scale by combining remote sensing, proximal sensing, and field measurements. You will develop and optimize machine-learning models

  • Ghent University | Belgium | 2 months ago

    of employment: Contract of limited duration →  Term of assignment: 2 jaar →  Wage scale: WM1 to WM4 (master degree or doctoral degree) →  Required diploma:Master or PhD ABOUT GHENT UNIVERSITY Ghent University is

  • Ghent University | Belgium | 2 months ago

    of limited duration →  Term of assignment: 2 jaar →  Wage scale: WM1 to WM4 (master degree or doctoral degree) →  Required diploma:Master or PhD ABOUT GHENT UNIVERSITY Ghent University is a world of its own

  • Ghent University | Belgium | 3 months ago

    obtain a PhD degree. The candidate will work as a doctoral researcher at the facilities of Orsi Academy, Melle, Belgium. The researcher is expected to join an international interdisciplinary research team

  • Ghent University | Belgium | 3 months ago

    technologies; you are capable to formulate research projects, to acquire the necessary funding for them, and to execute them successfully; you are capable to build your own research team, and to advise PhD

  • Ghent University | Belgium | 20 days ago

    learning, potentially inspiring novel paradigms that advance beyond traditional (silicon) computing. This PhD position aims to understand and advance in vitro neural models by means of quantitative

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