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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams, Saelens
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Education Alliance (SEA) program, comprehensive educational tools and resources developed and managed through the BioInteractive program, and student-centered initiatives managed through the Success in
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University professorship (m/f/d) in 'AI in Occupational, Social and Preventive Medicine' (salary gra
implementation of AI algorithms and tools for analyzing and predicting health-related events, process optimization and decision support in healthcare. Validation of models to ensure accuracy and reliability
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expertise from computer science and mathematics into the field of ocean sciences. The school’s interdisciplinary focus spans supercomputing, modeling, (bio)informatics, robotics, statistics, and big data
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Science or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. • An excellent
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detectors (Partial) automation of detector characterization for more efficient analysis Algorithm development: Development of a correction method based on information field theory for atmospheric image
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Computer Science, Information Theory, Physics or related fields High level of mathematical maturity Experience with topics related to quantum LDPC codes and decoding algorithms, or demonstrated ability and
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate
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algorithms for dynamic structured data, with a particular focus on time sequences of graphs, graph signals, and time sequences on groups and manifolds. Special emphasis will be placed on non-parametric