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20 Feb 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electronic engineering Researcher Profile
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8 Feb 2026 Job Information Organisation/Company KU LEUVEN Department KBI/FEB Research Field Computer science » Informatics Economics » Business economics Engineering » Computer engineering Economics
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, Interaction Design, Human-Computer Interaction (HCI), Participatory Design (PD) or alike. You must have a Master's degree in Computer Science, Information Science or equivalent (with a focus on learning
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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principled new models and methods, for modern machine learning problems. Machine learning recently has been largely advanced by differential equation-based frameworks, such as generative diffusion models
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ecological modelling. • Interest in undertaking field work and laboratory analysis (eDNA) methods to monitor and evaluate risks of algal blooms in reservoirs. • Familiarity with computer programming
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
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integrate innovative methods and automation into fungal research, advancing how we visualize, quantify, and interpret the hidden dynamics of mycorrhizal fungi. This enhances not only our mechanistic insights
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PhD position in Adaptive Protocols for Decentralized Wireless Networks - Secure Mobile Systems Group
associate will employ methods such as reverse engineering to understand and modify the behavior of off-the-shelf systems. This forms the basis for designing, implementing, and experimentally evaluating
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carcinoma as a use case. The successful applicant will develop Bayesian statistical and machine learning methods for treatment response prediction using clinical information, molecular characterizations