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12th December 2025 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Algorithmic Fairness in Recommender Systems Apply for this job See
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is not a standalone concept and has close connections to diversity, transparency and bias. In this position, the PhD candidate will work on algorithmic fairness in job recommender systems
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analytical skills, analyze data, assess different perspectives and draw well-founded conclusions Strong motivation to contribute to a good working and social environment In the evaluation of which candidate is
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, result-oriented Excellent analytical skills, analyze data, assess different perspectives and draw well-founded conclusions Strong motivation to contribute to a good working and social environment In
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analytical skills, analyze data, assess different perspectives and draw well-founded conclusions Strong motivation to contribute to a good working and social environment In the evaluation of which candidate is
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to work independently as well as in teams Work in a structured way, set goals and make plans to achieve them, result-oriented Excellent analytical skills, analyze data, assess different perspectives and
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analytical skills, analyze data, assess different perspectives and draw well-founded conclusions Strong motivation to contribute to a good working and social environment In the evaluation of which candidate is
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of Norway (RCN) and are supported by the Centre of Excellence funding Scheme by the RCN (the Centre for Algorithms in the Cortex), as well as the Kavli Foundation. The Zong group is further supported through
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analytical skills, analyze data, assess different perspectives and draw well-founded conclusions Strong motivation to contribute to a good working and social environment In the evaluation of which candidate is
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supervised deep learning algorithms for 3D laser data from forests Developing self-supervised deep learning algorithms for 3D laser data from forests Expand for a wider variety of downstream tasks focused